{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1数据加载\n",
    "# 2数据探索与预处理\n",
    "## 2.1数据特征探索\n",
    "## 2.2按照时间聚合目标值total_purchase_amt和total_redeem_amt\n",
    "## 2.3目标值可视化\n",
    "## 2.4准备目标值\n",
    "# 3模型训练与预测\n",
    "## 3.1模型导入与拟合\n",
    "## 3.2模型预测\n",
    "## 3.3预测结果可视化\n",
    "## 3.4预测结果提交"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['axes.unicode_minus'] = False#这句代码解决待会画图出来  坐标轴负号乱码问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1数据加载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "         user_id  report_date  tBalance  yBalance  total_purchase_amt  \\\n",
       "0              1     20140805     20385     20383                   2   \n",
       "1              1     20140808     20391     20389                   2   \n",
       "2              1     20140811     20397     20395                   2   \n",
       "3              1     20140814     20403     20401                   2   \n",
       "4              1     20140817     20409     20407                   2   \n",
       "...          ...          ...       ...       ...                 ...   \n",
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       "\n",
       "         direct_purchase_amt  purchase_bal_amt  purchase_bank_amt  \\\n",
       "0                          0                 0                  0   \n",
       "1                          0                 0                  0   \n",
       "2                          0                 0                  0   \n",
       "3                          0                 0                  0   \n",
       "4                          0                 0                  0   \n",
       "...                      ...               ...                ...   \n",
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       "2840418                    0                 0                  0   \n",
       "2840419                    0                 0                  0   \n",
       "2840420                    0                 0                  0   \n",
       "\n",
       "         total_redeem_amt  consume_amt  transfer_amt  tftobal_amt  \\\n",
       "0                       0            0             0            0   \n",
       "1                       0            0             0            0   \n",
       "2                       0            0             0            0   \n",
       "3                       0            0             0            0   \n",
       "4                       0            0             0            0   \n",
       "...                   ...          ...           ...          ...   \n",
       "2840416                 0            0             0            0   \n",
       "2840417             12500        12500             0            0   \n",
       "2840418                 0            0             0            0   \n",
       "2840419             31732            0         31732            0   \n",
       "2840420                 0            0             0            0   \n",
       "\n",
       "         tftocard_amt  share_amt  category1  category2  category3  category4  \n",
       "0                   0          2        NaN        NaN        NaN        NaN  \n",
       "1                   0          2        NaN        NaN        NaN        NaN  \n",
       "2                   0          2        NaN        NaN        NaN        NaN  \n",
       "3                   0          2        NaN        NaN        NaN        NaN  \n",
       "4                   0          2        NaN        NaN        NaN        NaN  \n",
       "...               ...        ...        ...        ...        ...        ...  \n",
       "2840416             0         61        NaN        NaN        NaN        NaN  \n",
       "2840417             0         60        0.0        0.0        0.0    12500.0  \n",
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       "2840419         31732       2298        NaN        NaN        NaN        NaN  \n",
       "2840420             0          0        NaN        NaN        NaN        NaN  \n",
       "\n",
       "[2840421 rows x 18 columns]"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据加载\n",
    "data=pd.read_csv('user_balance_table.csv')\n",
    "data#数据是读取进来了  但是里面有日期的格式 需要将日期格式读取进来 就是report_date那一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "scrolled": false
   },
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840417</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-08-31</td>\n",
       "      <td>525707</td>\n",
       "      <td>538147</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12500</td>\n",
       "      <td>12500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840418</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-07-24</td>\n",
       "      <td>20487121</td>\n",
       "      <td>20484824</td>\n",
       "      <td>2297</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840419</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-07-27</td>\n",
       "      <td>20462288</td>\n",
       "      <td>20491722</td>\n",
       "      <td>2298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>2298</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840420</th>\n",
       "      <td>28035</td>\n",
       "      <td>2014-03-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2840421 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id report_date  tBalance  yBalance  total_purchase_amt  \\\n",
       "0              1  2014-08-05     20385     20383                   2   \n",
       "1              1  2014-08-08     20391     20389                   2   \n",
       "2              1  2014-08-11     20397     20395                   2   \n",
       "3              1  2014-08-14     20403     20401                   2   \n",
       "4              1  2014-08-17     20409     20407                   2   \n",
       "...          ...         ...       ...       ...                 ...   \n",
       "2840416    28033  2014-08-25    550646    550585                  61   \n",
       "2840417    28033  2014-08-31    525707    538147                  60   \n",
       "2840418    28033  2014-07-24  20487121  20484824                2297   \n",
       "2840419    28033  2014-07-27  20462288  20491722                2298   \n",
       "2840420    28035  2014-03-05         0         0                   0   \n",
       "\n",
       "         direct_purchase_amt  purchase_bal_amt  purchase_bank_amt  \\\n",
       "0                          0                 0                  0   \n",
       "1                          0                 0                  0   \n",
       "2                          0                 0                  0   \n",
       "3                          0                 0                  0   \n",
       "4                          0                 0                  0   \n",
       "...                      ...               ...                ...   \n",
       "2840416                    0                 0                  0   \n",
       "2840417                    0                 0                  0   \n",
       "2840418                    0                 0                  0   \n",
       "2840419                    0                 0                  0   \n",
       "2840420                    0                 0                  0   \n",
       "\n",
       "         total_redeem_amt  consume_amt  transfer_amt  tftobal_amt  \\\n",
       "0                       0            0             0            0   \n",
       "1                       0            0             0            0   \n",
       "2                       0            0             0            0   \n",
       "3                       0            0             0            0   \n",
       "4                       0            0             0            0   \n",
       "...                   ...          ...           ...          ...   \n",
       "2840416                 0            0             0            0   \n",
       "2840417             12500        12500             0            0   \n",
       "2840418                 0            0             0            0   \n",
       "2840419             31732            0         31732            0   \n",
       "2840420                 0            0             0            0   \n",
       "\n",
       "         tftocard_amt  share_amt  category1  category2  category3  category4  \n",
       "0                   0          2        NaN        NaN        NaN        NaN  \n",
       "1                   0          2        NaN        NaN        NaN        NaN  \n",
       "2                   0          2        NaN        NaN        NaN        NaN  \n",
       "3                   0          2        NaN        NaN        NaN        NaN  \n",
       "4                   0          2        NaN        NaN        NaN        NaN  \n",
       "...               ...        ...        ...        ...        ...        ...  \n",
       "2840416             0         61        NaN        NaN        NaN        NaN  \n",
       "2840417             0         60        0.0        0.0        0.0    12500.0  \n",
       "2840418             0       2297        NaN        NaN        NaN        NaN  \n",
       "2840419         31732       2298        NaN        NaN        NaN        NaN  \n",
       "2840420             0          0        NaN        NaN        NaN        NaN  \n",
       "\n",
       "[2840421 rows x 18 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv('user_balance_table.csv',parse_dates=['report_date'])\n",
    "data#user_id就是用户 report_date是日期 tBalance是今日余额  yBalance是昨日余额  total_purchase_amt 今日总购买量（=直接购买+收益）\n",
    "#direct_purchase_amt是直接购买  purchase_bal_amt今日支付宝余额购买量  purchase_bank_amt今日银行卡购买量 \n",
    "#total_redeem_amt今日总赎回量（=消费+转出） consume_amt今日总消费量 transfer_amt今日转出总量   \n",
    "#tftobal_amt今日转出到支付宝余额总量 tftocard_amt今日转出到银行卡总量   share_amt今日收益\n",
    "#category1 category2 category3 category4分别表示类目1 2 3 4 消费总额\n",
    "#其中 total_purchase_amt 和 total_redeem_amt 是我们要预测的目标值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2数据探索与预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1数据特征探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-07-01      441\n",
       "2013-07-02      480\n",
       "2013-07-03      499\n",
       "2013-07-04      523\n",
       "2013-07-05      544\n",
       "              ...  \n",
       "2014-08-27    12527\n",
       "2014-08-28    12557\n",
       "2014-08-29    12596\n",
       "2014-08-30    12603\n",
       "2014-08-31    12614\n",
       "Name: report_date, Length: 427, dtype: int64"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['report_date'].value_counts().sort_index()#2840421个数据里面 时间只有427个  时间最早是从2013-07-01  最晚是到2018-31-31"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2840421 entries, 0 to 2840420\n",
      "Data columns (total 18 columns):\n",
      " #   Column               Dtype         \n",
      "---  ------               -----         \n",
      " 0   user_id              int64         \n",
      " 1   report_date          datetime64[ns]\n",
      " 2   tBalance             int64         \n",
      " 3   yBalance             int64         \n",
      " 4   total_purchase_amt   int64         \n",
      " 5   direct_purchase_amt  int64         \n",
      " 6   purchase_bal_amt     int64         \n",
      " 7   purchase_bank_amt    int64         \n",
      " 8   total_redeem_amt     int64         \n",
      " 9   consume_amt          int64         \n",
      " 10  transfer_amt         int64         \n",
      " 11  tftobal_amt          int64         \n",
      " 12  tftocard_amt         int64         \n",
      " 13  share_amt            int64         \n",
      " 14  category1            float64       \n",
      " 15  category2            float64       \n",
      " 16  category3            float64       \n",
      " 17  category4            float64       \n",
      "dtypes: datetime64[ns](1), float64(4), int64(13)\n",
      "memory usage: 390.1 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()# 'report_date'这个字段的类型是datetime64[ns]  其他的都是整形和浮点型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2按照时间聚合目标值total_purchase_amt和total_redeem_amt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>32488348</td>\n",
       "      <td>5525022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>29037390</td>\n",
       "      <td>2554548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>27270770</td>\n",
       "      <td>5953867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>18321185</td>\n",
       "      <td>6410729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>11648749</td>\n",
       "      <td>2763587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>302194801</td>\n",
       "      <td>468164147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>245082751</td>\n",
       "      <td>297893861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>267554713</td>\n",
       "      <td>273756380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>199708772</td>\n",
       "      <td>196374134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>275090213</td>\n",
       "      <td>292943033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt  total_redeem_amt\n",
       "report_date                                      \n",
       "2013-07-01             32488348           5525022\n",
       "2013-07-02             29037390           2554548\n",
       "2013-07-03             27270770           5953867\n",
       "2013-07-04             18321185           6410729\n",
       "2013-07-05             11648749           2763587\n",
       "...                         ...               ...\n",
       "2014-08-27            302194801         468164147\n",
       "2014-08-28            245082751         297893861\n",
       "2014-08-29            267554713         273756380\n",
       "2014-08-30            199708772         196374134\n",
       "2014-08-31            275090213         292943033\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#这个时候可以根据时间来做一个分组聚合操作\n",
    "total_balance=data.groupby(['report_date'])['total_purchase_amt','total_redeem_amt'].sum()\n",
    "total_balance#这里果然是427行  然后对应的天数 total_purchase_amt求和了  total_redeem_amt也求和了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>32488348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>29037390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>27270770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>18321185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>11648749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>302194801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>245082751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>267554713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>199708772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>275090213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt\n",
       "report_date                    \n",
       "2013-07-01             32488348\n",
       "2013-07-02             29037390\n",
       "2013-07-03             27270770\n",
       "2013-07-04             18321185\n",
       "2013-07-05             11648749\n",
       "...                         ...\n",
       "2014-08-27            302194801\n",
       "2014-08-28            245082751\n",
       "2014-08-29            267554713\n",
       "2014-08-30            199708772\n",
       "2014-08-31            275090213\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purchase=total_balance[['total_purchase_amt']]\n",
    "purchase#这样就有了一个新的dataframe 专门存储 某天的购买  这个也是我们要预测的这一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th></th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>5525022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>2554548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>5953867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>6410729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>2763587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>468164147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>297893861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>273756380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>196374134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>292943033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_redeem_amt\n",
       "report_date                  \n",
       "2013-07-01            5525022\n",
       "2013-07-02            2554548\n",
       "2013-07-03            5953867\n",
       "2013-07-04            6410729\n",
       "2013-07-05            2763587\n",
       "...                       ...\n",
       "2014-08-27          468164147\n",
       "2014-08-28          297893861\n",
       "2014-08-29          273756380\n",
       "2014-08-30          196374134\n",
       "2014-08-31          292943033\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "redeem=total_balance[['total_redeem_amt']]\n",
    "redeem#这个dataframe专门存储赎回 也就是当天的赎回（消费+转出）  这个也是我们要预测的一列"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3目标值可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "#指定区间范围内的数据,进行可视化\n",
    "def plot_stl(data):\n",
    "    #STL返回三个部分：trend(趋势),seasonal(季节),residual(残差)\n",
    "    result=sm.tsa.seasonal_decompose(data,period=30)#我们的数据量只有从2013-07-01到2014-08-31一年多的数据量 而且我们要预测的仅仅是下一个月\n",
    "    #所以这里的参数period=30 算是一个周期      如果像股票那样周期是年的  可以设置成200\n",
    "    #可视化\n",
    "    fig=plt.figure(figsize=(12,8))\n",
    "    ax1=fig.add_subplot(311)\n",
    "    ax2=fig.add_subplot(312)\n",
    "    ax3=fig.add_subplot(313)\n",
    "    #result里面包含三个部分 trend(趋势),seasonal(季节),residual(残差)\n",
    "    result.trend.plot(ax=ax1,title='Trend趋势')\n",
    "    result.seasonal.plot(ax=ax2,title='Seasonal季节')\n",
    "    result.resid.plot(ax=ax3,title='Resid残差')\n",
    "plot_stl(purchase['total_purchase_amt'])#这里三张图的横坐标都是表格中的日期类型  从2013年7月到2014年8月"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QQ/EMfnH1yehsDE60RMIBv1myHdv74rjrU6e7+la+hVOb8Km3zcLvXtqBK0+ZhsWz6Ca38aDqPr1Ooe4NBEEQhw/Ldg7ik79/E+GAF9+8dAFOndmKqS1h/H1FN375/Fakc3mcPrsdv7jqJHgO8cshkpk8rvz1q1jfMwoA6GoKYTiZwdxJDbjn+rPQEKTT9Icya7tHcMUtr+Jdx03GzR89ZaLl1Ew8ncPFP38RHsbw+FfPpflXJXVvWVYJ5PQSBEEcHgzGM7j0Fy8i7PfiL589E1NbwhMtqWbi6RxW7x3BzPYIpjSHsGRTHz7zh2W4YH4nbv3Y4kPecT9SiaVzuOyml5DKKnj8q+cesrW8lfLmzkFc9dvXcPmJU3Hjh06Ez8OQyioIB9wbxT7Y1L1lGUEQBHH4k80reHLtfoT9XjAG3PHKDgzFs7j9C6cdFg4vAESDPpx1dLv+9wsWTMJ33nMsvvvIevz2xe34p/PpCtlDgXQujzV7R7B7MIHuoSTuXbYH+4aTuOf6sw4bhxcATpvVhq9eeAx+9uxmbNo/hkxOwc6BOD59zmz88zuPoV6+NUKjRxAEQRQwlsriC39+Cy9tMW6Z93oYvvfe4w77G6Q+cfYsLNs1hB8/tREnHdVicoqJg0syk8ctS7bidy9tRyqr6F8/fXYb/uf9x+P02Ydf7etXL5qHBVMa8YPHN6C9IYhF05vxu5d2YNmuIdz92TNdXbs80VB5A0EQBGEir3B85NalWL57CN9773FYOLUJuTzH8dOajphIUyydw3tvfhmjyRwe/8o5mHQQr68lVPIKxwdueQWr947gskVTcNmiqVjQ1YjWSEC/0vdI4fE1PfjiX97Cu4+fgps+cjK8VHZTlFLlDVX36SUIgiAOT257aTve2DmIH125CNeeOROnzGjF6bPbjhiHF1BvdPvNtacins7hhnupn+9E8Le39mL13hHc+KETcfNHT8Elx3dhVkf0iHN4AeDdJ0zBNy9dgMfW9OCjv1uK7uHkREtyJeT0EgRBEDqb9o/hJ09vxsXHTcaVp0ybaDkTyjGTG/Gfly/Eq9sG8Jc3dk+0nCOKVDaPnz6zGSce1XLEz0PBZ8+dgxs/dCLWdo/gkp+/iIdWdk+0JNdx5GzbCYIgiJJk8wr+5b6VaAz58P0PnAD1tvkjm6tOOwqPrenBDx7fgPPmdWJGewQA8NbuITy0ohunzGzFRcdORpTaS9WVe9/cg56RFH521Uk0DzUYY/jgqdNx+qw23HDvCnz1npVYv28U37h0QVVjtLZ7BL/+xzYMJzKY3RHFnI4GHD+tGafMaIHPa8REU9k8Nu4fw4nTm13/b0E1vQRBEAQA4GfPbMYvntuC31x7Ci45fspEyzlk2DuUwHtuehnt0QDu/dxZWL5rCDfcuwKZnAKFA8dMbsCfPn0G1f3Wkffc9BIYAx798rkTLeWQJJdX8N1H1uFPS3fjqsVH4dPnzkbfWBqr947A72U4eUYLTp1Z/JDffW/uwb8/sBpNIR9mdzZgR18Mo6kcAKA57Md1b5uF6942G9v6YvjmA2uw6cAYzpjdhu9/4ATMndRwsH7NqqA+vQRBEERJVu8dxgdueRXvPXEqfnbVSRMt55Bj2c5BXHPb68jkFXAOHD+tCb//5OlYtWcYX7lnBSY1BnHf58/CpEZyfGtlQ88oLv3FS/ju5QvxybfNnmg5hyycc/zgiY343UvbYefKnTyjBWfNacfps9tw3rxOvef0roE4Lv3FSzhxegt++/FT0RTyg3OOgXgGb+4YxIMruvH0+gP6+3Q0BPHR04/CH5fuQiTgw5M3nIvGQ/i2RXJ6CYIgiKKksnlc9suXMZbK4ukb3n5EHhRywmvbBvDshgM4YVoz3nXcZP1g3/JdQ7j2ttcxv6sR91xPLaVq5X8eXY+7XtuJ1//fRYdVD97xYv9ICs9v7EVnYxCnz25DXuF4ZNU+3P3GbmztjSGncBwzuQH/+4ETML+rER+/4w1s7Y3hqRvOK9pv+40dg3h9+wCmtoTxjgWT0BoNYPmuIXzoN6/iw4uPwg+vXHSQf0vnkNNLEARBFOXXS7bhR09uxJ3XnYbz50+aaDmu5Mm1+/H5Py3HB0+djhs/dOJEyzlk2XJgDH9f2Q0vY1g0vQXb+mJYuWcY2/piuPKU6TjxqBZ87o/LceacNvz2Y7Z+C1EB6Vwej63uwc+f3YKekSSmtoSxdyiJm64+Ge9ZVHkJ04+e3IhfL9mGGz90Ij546vRxUFw7dCMbQRAEYYuicNzz5m6cMbuNHN4auOT4Lnzpgrm4+YWteN9JU3HuvM6JllQXhhMZ/GNzH/YMJrB3KInu4ST2DiUxlMiAAZjZHsWi6c2Y0RZByO/FaCqLDT1jCPs9uGzRVJwzt0NPq9/03Bb89JnN8HoYOOcQXeCOagujPRrED57YCACY0RbBv75r/gT9xocXQZ8XV5wyHRcumIwv3f0WVu0Zxl3XnY5z5nVU9X43XDQPa/aO4N/vX4WGoA+XHN9V9LWcc2zpjaFvLI2gz4P5XY0TXhZBkV6CIIgjmFe39eOjv3sdP7vqRHzg5EMzcuMWUtk8Lv3FS+Cc48kbzqupzGHPYAIPrujG6zsGEPZ7sXhWGz5zzmzTqfrxJJnJ4z8fXosHV3Qjm1f9hI6GAKa1RjC9JYz2hgAUzrH5QAzr940ils7pPzutJYzRVBZjqRwuOnYy/ut9x+GRVfvwgyc24gMnT8O33nMs/F4PNu0fw9GdUbQ3BME5xyOre7ChZxRfvGAuGqgbRt3hnCOdU2ouv4mnc7j29texrnsUd3zyNFsH+tn1B/DTZzZjfc+o6esz2yM4bmoTfnbVSQj6xqcMiMobCIIgCFu+es8KvLCxF2986yKqRa0DL2/px7W3v46vXDgP//LOY6p6j7d2D+Hjt7+BeCaHhVOakMkp2NIbw4lHteA3156CKc1qHeZLW/pw+8s7EA36cN68Dnzw1KPK3tQ1EEsj5PeWbLHWO5rCZ/6wDGu6R/DxM2fiilOmY35XY9H5wTnHcCKLbF5BJOhDQ9CHVDaPPy3dhR8+sRE5LaR70bGT8JtrTz1ojjsxfgwnMrj61qXYPZjA7Z84zXRV952v7MB3H1mPozujuO5tszFvUgNi6Rw29Ixifc8oDoym8cA/nT1u2sjpJQiCIAoYTmRw+v8+h4+cdhS+977jJ1rOYcNX71mBJ9bsxxM3nIujOxvw0MpuPLxyH85fMAkfOHlaySjmun0juPq3S9HWEMAfP3WG3hf4kVX78P/+tgbtDQHced3pWLV3GF/76yq0R4PweRn2DiUxpzOKY6c0Yf7kRrzvpKmY2R7V3/fR1fvwg8c3ons4CZ+HYdH0Zpw5px0XLZyMU2a06q/bO5TANbe9jr6xNG66+mRctHByTWPx1u4hvLZtACdOb8GZc9rI4T2M6B1L4aO/ex27BuL4+iULcPKMFvzhtV14aOU+vGvhZNz0kZMnZCNNTi9BEARRgIjIPP6Vc7FwatNEyzls6BtL48KfLEFHYxALuhrx+Jr9aIn4MZzIYuGUJtzzuTPRZFPbGEvncNlNLyGdU/DAP51dcLJeRIBFKcHJM1pw53Wnoynkw+Nr9uMPr+1E71gaOwfi4Bz4xFkz8c/vPAYPrujGfz26HoumNeOyRVMxlMhg6fYBrN47gpzCcerMVrz7hCnI5BTc/vJ2ZHIK7vzU6SZnmCDsGElm8cU/v4WXt/YDAII+Dz533hx85cJ5E7bBIaeXIAiCMME5x6W/eAkBnwcPf+mciZZz2PGMVtO4dyiB9580Df9x+UL8Y1Mf/unPy3HyUa2461OnIxwwomCcc9xw70o8smof7v3cWThtlv3FAuv3jeKFTb04urMB58/vtI2k7RtO4tYXt+POV3fqX3v7MZ34zbWnmj4zls7hgeV7cddrO7G9Lw4AOGduB7592bFY0EWbIMIZisKx6cAYdg3EccL0Fkwr0gbtYEFOL0EQBGFi5Z5hvP9Xr+D7Hzge15wxc6LlHDE8smofvnLPClwwfxJ++7FT4deiYX9dtgf/dv9q/Os7j8GXL5xXl89asqkXb+4cxFlzOnDW0e0l6327h5NIZfM4uvPQvm2LIMpBLcsIgiAInbzC8dNnNiPs9+K9J06daDlHFJefOBUjySy+/fe1uOGelfjJh0/EzoE4/uOhdThrTju+cMHcun3W+fMnOW5DN9HROYI4GJDTSxAEcQTBOcd/P7oeL27uw/c/cPyE9808Ern2zJlIZvL4/uMbsHH/KPYMJtEU9uHnV59UtvsCQRDVQ04vQRDEEUImp+A/H16Lu9/Yg0+fM5vKGiaQz543B9Nbw/jmg2vwvpOm4msXz8fkptBEyyKIwxpyegmCII4AFIXj839ajuc39uIL5x+Nr9GNVxPOpSdMwSXHd4Exiu4SxMGAnF6CIAiXsHrvMH74xEbsGUrg7Dkd+M7lCx3fXPXbF7fj+Y29+O7lC/HJt80eZ6WEU8jhJYiDB3WJJgiCcAGpbB5fuXsFNh+I4diuJvx1+R5cdtNLWL13uOzP/mNzH258ehPec8IUfOLsWeOulSAI4lCEIr0EQRAu4JYXtmLnQAJ/+vQZOGdeB97YMYgb7lmBK255Ff928Xx89tw58EiHoPYMJvDo6h4onOMXz27BMZMb8YMrT6DIIkEQRyzk9BIEQRziLNs5iF//Yxvef9JUnDOvAwBw+uw2PP7Vc/GNB9bgB09sxMtb+/Hzq05Ce0MQW3tj+OjvlqJ3LA0AOPGoFvzhutNtbwEjCII4UqDLKQiCIA5BOOfoG0tj50ACX/jzcjQEfXjoi+egOeIveN1f3tiN/3pkPSY3hXD16Ufhdy9uh9fDcOd1p6M1GkBXU4haYREEcURAl1MQBEG4BM45bnx6E+59cw/6YxkAQEPQh3uuX1zg8ALqQahrzpiJY6c04TN3LcP/PbkJZ85pw/c/cALdrkUQBCFBTi9BEMQhxE3PbcWvXtiGi46dhHPmdmB6awTHT2tGV3PpHq6nzGjFY185B3uHklg8s5VqdwmCICxU5fQyxpoB3KP9fAzAVZzzTD2FEQRBHGk8unoffvbsZlx5ynTc+KFFFTuuU5rDmNJM18kSBEHYUW3LsmsA/JRz/k4A+wFcUj9JBEEQRx4HRlP41oNrceJRLfghdVkgCIKoO1VFejnnt0h/7QTQK3+fMXY9gOsBYMaMGVWLIwiCOBLI5hV87a+rkM7l8dMPnwi/l1qoEwRB1JuaLCtj7CwArZzzpfLXOee3cs4Xc84Xd3Z21iSQIAjicEZROP79/tV4aUs//vPy4+jwGUEQxDhR9UE2xlgbgF8CuLJ+cgiCII4sfvvidjy4ohtfe9cx+MjplBkjCIIYL6o9yBYAcB+Ab3LOd9VXEkEQxKHJYDyDf/vrKmzoGQVjDMdNbcK7T5iC9500taoa3N6xFG5+fgsuOnYyvnjB3HFQTBAEQQiqLW/4NIBTAXyLMbaEMXZVHTURBEEccuwdSuDKX7+Kl7f248w57ThlZivW94zihntX4qrfLsXeoUTF7/mzZzYjnVPwrfccSwfXCIIgxplqD7L9GsCv66yFIAjikERROP753pXoj6Xx58+cgcWz2vSv/3X5HvzPYxtwxS2v4s7rTsfCqU2O3nNr7xjufXMPPnH2LMzuiI6nfIIgCAI1HmQjCII4Evjz67vw5s4h/MdlC3WHFwA8HoarTpuB+z9/NjyM4QO3vIJfvbAVmZxS9j1/9uwWhPxefInKGgiCIA4K5PQSBEGUoHs4iR8+sRHnzuvAB0+dbvua+V2NePhLb8M7FkzCj5/ahPfc9BLe2DFY9D039IzisdU9uO5ts9DeEBwv6QRBEIQEOb0EQRBF4JzjWw+uAQfwvx8ofWHEpKYQfn3tqbjjk4uRyORx1a2v4VcvbAXn3PS6FbuHcP0fl6Ex5MNnz50zzr8BQRAEIai6ZRlBEMThTCydw60vbseSTX347uULcVRbxNHPvWPBZJz5L+34xgNr8OOnNuGFjb342Fkzkcjk8cz6A1iyqRdTmsO461OnoyUSGOffgiAIghCQ00sQBCHRM5LEHS/vwD1v7sFYKoeLjp2Mj501q6L3iAR8+MXVJ+HMOe345fNb8NV7VgIAJjUG8U/nH43rzzsazWF//cUTBEEQRSGnlyAIQmPj/lFc87vXMZzM4t0nTMGn3jYLJ89oreq9GGP46Bkz8MFTp2PdvhF0NAQxtSUMr4dakxEEQUwE5PQSBEEAWLdvBNfe9jqCPi+euuFczJ3UWJf3Dfg8VTvOBEEQRP0gp5cgiCOeNXtHcO3tr6Mh6MNfPnsGZrZT31yCIIjDDXJ6CYI4oukdTeHjd7yOxpAPd3/2TMcH1giCIAh3QS3LCII4YuGc498fWI1EJo87rzudHF6CIIjDGHJ6CYI4YnngrW4s2dSH//fuYzF3UsNEyyEIgiDGEXJ6CYI4IlEUjluWbMVxU5vwsTNnTrQcgiAIYpwhp5cgiCOSFzb1YntfHNefNwceaiNGEARx2ENOL0EQRyS/e2k7pjSH8O4Tpky0FIIgCOIgQN0bCII4LNnaG8PLW/qwoz+OqS1hnDyjFafNagVjDPe8sRtLtw/i2+85Fn4v7f0JgiCOBMjpJQjisGLXQBz/89gGPLP+AAAgGvAinskDAKa3hnH67DY8uqoH587rwHVvmz2RUgmCIIiDCDm9BEEcNqzcM4xP3fkmsnkFN1w0Dx9afBSmtYQxksji+U0H8MiqHjy3oRfTW8P45UdOpiuBCYIgjiDI6SUIwvUoCsddr+3ED5/YiMlNIdz1qdMxu8O4Va054scHTp6OD5w8HZxzcA46vEYQBHGEQU4vQRCuIK9wPLyqG0+s2Y8Ve4aRyuaRy3Nk8wpyCgcAXDC/E//3wRPR2Rgs+j6MMTDydwmCII44yOklCOKQ540dg/j239dg84EYprWEcd68TjSGfAj4PPB5GPxeD+ZNbsB7TpgCRh4tQRAEYQM5vQRBHLLk8gpuem4Lbn5hK6a1hvHra07BJcd3kWNLEARBVAw5vQRBHHKMJLNYv28UP35qI97aPYwrT5mO773vODQEyWQRBEEQ1UFPEIIgDgl6x1L4xbNbsGRTH7qHkwCAxqAPv7j6JLzvpGkTrI4gCIJwO+T0EgQxriQzeby4pQ9v7RrC/K5GHD+tGQzAU+v2Y/muIQR9XgzGM1jTPYKcouBdC7twzZkzcOyUJpw0vQWt0cBE/woEQRDEYQA5vQRBjBu9oylc/bul2N4Xh4cBWpMFnfmTG6FwjtZIAFecMg2fOXeOqdUYQRAEQdQLcnoJghgX+mNpfPS217F/JIXffuxUnD+/E1sOxLC9P45sTsFps9owoz0y0TIJgiCIIwRyegmCqDuD8Qyuve117B1K4M7rTseZc9oBAMdPa8bx05onWB1BEARxJEJOL0EQdUNROJ5atx8/fnoTuoeSuOOTp+kOL0EQBEFMJFU7vYyxyQDu55yfW0c9BEG4kHQuj6fXHcDNz2/FpgNjmNMRxe8/eRrOntsx0dIIgiAIAkCVTi9jrBXAXQDoxAlBHIHsHUrg8TU9eH37IEZTWWzcP4axVA5zOqP4+VUn4fITp8LroQskCIIgiEOHaiO9eQBXAXiojloIgjjESWXz+O0/tuNXS7Yik1Mwd1IDJjUGcclxXXjPoik4d14nObsEQRDEIUlVTi/nfBRA0atAGWPXA7geAGbMmFGtNoIgDhE453hy7X787xMbsGcwicsWTcHXL1mAo9qo+wJBEAThDsblIBvn/FYAtwLA4sWLeZmXEwRxCLOtL4ZvPbgGS7cPYv7kRvzp02fgnHlUq0sQBEG4C+reQBCHCWOpLJZuH0Qik0PI70VrJIDWiB/TWyMIB7z66/pjafzk6c14bVs/FnQ14YpTpuGdCycXZG4453h0dQ++8cBq+H0e/Pf7j8dHTjsKPq/nYP9qBEEQBFEz5PQSxGHA8xsP4P/9bS32j6YKvufzMCyc2oSj2iIYTWbxxo5B5BWO847pxOq9w3hy3X6cNacdi45qRkPAh5zCkVc4Xtraj1V7hnHyjBbccs0pmNIcnoDfjCAIgiDqQ01OL+f8/DrpIAiiQjI5Bf/Y3IfbXtqO13cM4pjJDfjxh07HlOYQUlkFQ4kMBuMZbD4whpV7hrF+3yj8XoaPnjED1545E0d3NiCbV3DXqzvxx6W7sHzXEDJ5BQDg9TDMaIvgfz9wAj546nQEfBTdJQiCINwN43x8S24XL17Mly1bNq6fQRBHEgOxNP7w2i784bWdGEpkMakxiC+cfzQ+csYMBH3e8m9QBEXhUDiH18OKHlIlCIIgiEMZxthyzvliu+9ReQNBHMLkFY4d/TGs7xnDun0jWLFrGMt2DULhwEXHTsZHzzgK587rhL8OdbYeD4MH5OwSBEEQhyfk9BLEBDCWymLlnmH0DKcwmsrC7/Ug4PPAyxgGExnsGohj/b5RbDowhlRWLTnwexkWdDXhixfMxeUnTsUxkxsn+LcgCIIgCPdATi9BHEQ2HxjDz57ZjKfW7YdSorKoJeLHwilNuOaMmVg4pQnHTmnC3EkNVFtLEARBEFVCTi9BjBOpbB79sTT6Yxn0j6XxyOp9eHjVPkQDPnz23Dk4Z14HZrVH0RTyI6coyOY5coqC1kgA0SAtTYIgCIKoJ/RkJYg6MZLM4q5Xd+LlLf3YsH8UY6mc6fthvxefO+9ofO68OWiNBiZIJUEQBEEcmZDTSxB14Ol1+/Fv96/GSDKLk45qwftPmoau5hA6GgLoaAiioyGIWR1RNIf9Ey2VIAiCII5IyOkliBp5c+cgvnT3CizoasQPrjgBx01tnmhJBEEQBEFYIKeXIGpgbfcIPvuHZZjeEsZd151OZQsEQRAEcYhCTi9BVAjnHHuHkli+awj/8dBaNIb8uOtT5PASBEEQxKEMOb0E4YC9Qwk8troHy3cN4a3dQ+iPZQAAM9sj+NOnz8BRbZEJVkgQBEEQRCnI6SWIEvSOpfC9h9fjibU9UDgwuyOK847pxCkzWrFoejMWdDVR71yCIAiCcAHk9BJEER5f04NvPbgGiUwen3/70bjmzJmY1hKeaFkEQRAEQVQBOb0EYWHPYAI3Pr0JD63ch0XTm/HTD5+EuZMaJloWQRAEQRA1QE4vccQzEEvj2Q0H8NKWfuwdSmJN9wi8jOGrF87Dl94xF34vlS8QBEEQhNshp5eoiGxeQc9wCrsHE9g3nERbNICjJzVgZlsEHg+baHmOGU5k8MrWATy2Zh+eWX8A2TzHlOYQ5nRG8ZlzZ+O6s2ejqzk00TIJgiAIgqgT5PQSBSQzeSzZ1IuHV+3Dmu4R9Iyk0BBUp8poKgvOC3+mIejDwqlNWDilCXM6o5jUGEJz2K/+F/Ej5PNg5Z5hvLFjEOv2jWI0lQVjDJMbg5jdGcVxU5tx/NQmzGqP6s4z5xyprIKgz1PUoU5m8nhr9xBe2zaAN3YMomc0iWRGQUvEj7ZoAM1hPxKZHEaSWYwks1AUIJ7JYTiRBQC0Rvz4+Fmz8IGTp+G4qU1gzD2OO0EQBEEQziGn9wiBc449g0ks3z2IsVQOPo8HU1pC6GwIIuT3YjiRweq9I1iyuQ9Ltw8gk1MwqTGIM+e0Y2pLGIlMDgxAc9iP6a0RHNUWwbSWMPrjaWw5MIZ1+0axbt8o7lu2B4lMvqiOgNeD+V2NaG8IIK9w7OiP44VNvcjmVU/a52FojQaQzSsYS+WQVzh8HoZprWEsntmG+V0NCHg92HRgDKv3jmDT/jHkFA6vh+H4ac1YPLMNQZ8Hw4ksBuMZ7BlMIBr0YVJjCHM7G+DzehD0eTCzPYKTZ7Ti5KNa4KPyBYIgCII47GHcLmxXRxYvXsyXLVs2rp9BqKSyeazeO4LtfTEMxDNoDvsBADv743huYy929MfLvseczigumD8JFy6YhDPmtMNbYckC5xx9Y2n0jqUxqkVXR1NZjKVyOHZKExbPakXQ5zX9TCanYEvvGNZ1j2LnQBwDsQwCPg8aQz40hHyIpXLY1hfD6zsG9Qhtc9iPRdObcfy0Zpw+qw2LZ7WiMeSvSCtBEARBEIcXjLHlnPPFdt+jSO8hDuccI8ksMjkFQZ8XjSEfPB4Gzjn6Yxms3TeCN3cM4s2dg1i1ZwSZvFLwHn4vw5lz2vHJs2fhjDlt6GwIIp1T0D2cxGA8g1Q2j9ZIALM7ojVfssAYw6SmECY1Oa+HDfg8OG5qM46b2lzydZxzxNI5pLIKOhoCVIpAEARBEIRjyOmdANK5PLqHkugbS2MkmcVwMovRZBbDiSwG4mn0jUn/xdJ66h9QHdhIwIdMTkEyq5YR+DwMx01rxifOnonTZrXh2ClN6GwMqjWsnGNSY8g2YjvVZT1nGWNoDPnRSOfLCIIgCIKoEHJ6qyCVzWN7XxybD4xh84ExDCUySOcUhPxetEUCmNYaxrSWMKa1hjGpMYid/Qms3DuMVXuGsXrvMLb0xmwPg3kY0N4QREdDEJ2NQcyd1IjOxiA6GgII+b1IZfMYjGcQT+fg93owvTWMYyY34qQZLYgECv8pQ35v4YcQBEEQBEEcgZDTayGXV9AzksKugQQ2HxjDmzsH0T2cRCyVw2gqh1g6i1TWKCHwexlaIgEEvB6kc3kMJbLIK/Z10m3RAE6c3oxLjuvCzPYoJjUF0RIOoCXiR1PYj8agz1VtvwiCIAiCINzCEev0DsYz2NAzir1DCXQPJbFnKIkNPaPY2htDTnJaj2oL4+jOBsxsj6Ih6ENTyIfGkA+zOqKYP7kRszqipssLcnkF+0dT6B5Kons4if2jKcxoi+DE6S2Y3hqmOlSCIAiCIIgJ4LB2ehWFYziZxb7hJLb1xbCtN4ZNB8awtnsU3cNJ/XWMAZMbQ1gwpREXLJiEWe0RzGiLYk5nFJMrOJAFAD6vB9NbI5jeWtuBMIIgCIIgCKJ+uNrpVRS1s0HPSArre0axbt8INh8YQ99YGoPxDAbjGciVBh4GzGyP4uQZLfj4WTNx3NRmzGyPoKs5RFfNEgRBEARBHMa41ulVFI7533nC1Nkg7PfimK5GzO6IYvGsNrRHA2iPBjC5KaReldseKegRSxAEQRAEQRz+uNbp9XgYbrjoGIT9XnQ2BnHslCbM7ohWfJkCQRAEQRAEcfjjWqcXAL54wdyJlkAQBEEQBEG4gKoLWRljtzPGXmWMfbueggiCIAiCIAii3lTl9DLGrgDg5ZyfDWAqY2xefWURBEEQBEEQRP2oNtJ7PoD7tD8/D+Ac+ZuMsesZY8sYY8v6+vpqkEcQBEEQBEEQtVOt0xsF0K39eRTAZPmbnPNbOeeLOeeLOzs7a9FHEARBEARBEDVT7UG2GICw9ucGlHCely9fHmOMbarycw4VmgGMTLSIGnHz79ABoH+iRdSIm8ffzdoBmj8Tgdv02uHmeXM4jL+bfwc3zx2Bm8d/frFvVOv0Loda0rAUwIkASjm1mzjni6v8nEMCxtitnPPrJ1pHLbj5d2CMLaM5NHG4WTtA82cicJteO9w8bw6T8Xft7+DmuSNw+/gX+161Tu/fAbzEGJsK4FIAZ1b5Pm7hkYkWUAcOh9/Bzbh5/N2s/XDBbf8GbtN7uHE4jP/h8Du4mcNy/BnnvPyr7H6QsVYA7wTwIud8f4nXuX7HQ0wsNIeIWqD5Q1QDzRuiWmjuTCylxr/qyyk450MwOjiU4tZqP4MgNGgOEbVA84eoBpo3RLXQ3JlYio5/1ZFegiAIgiAIgnALVd/IRhAEQRAEQRBuoe5OL2Psu4yxa0t8f0m9P5NwP4yxBsbYg4yxVxhjdzHGbEtvGGMnMcZOOsjyCBdRzgYRhIAx1sYYizHGQhOthXAv5Pe4B4r0EocKXwawhXP+NgBBAB8u8rqTtP8IgiBq5Z1Q7c15Ey2EIIjxp+qDbGX4LmNsL+d8CWPskwDAOb9znD6LODw4A8Bt2p9fBnAaY+y9AKYDGIbqBH8HwAcAgDH2Mc75hROgk3AJjLHHAYQA7OKcX8cY+y4AP9Qe480ALinVeYY4IrgEwK8AXMIYOxuqHYoA6ANwNec8p0XpHgJwHed80YQpJQ51yO9xARTpJQ4VGgHEtT8nANwAYBXn/BwADwA4nnP+TQA/BPBDcniJMsyG6sxcCmAWY0xclT6Xc/52AH8B8I6JEjdeMMY8jLEAY6yRMTaNMXY8Y+xSxthXGWNXFfmZqxhjd0t/380YO+bgqZ5QzgLwPwCEPXlJmx8HALxP+9oUAJwcXoJwP3VxehljVzPGzpe+lJf+HAZBlGcU6pXWABAFcCeAN7S/3wngzYMviXALNjYoB+AzAP4MoA2GHfqD9v9eAAGb9/lXzenbzhi7bPwU1wZj7E4RTZK+FgGwEsBLAP4G4Emom8RFUNfXAem1XqluPqP9J8hq/0FzoA/L4AhjbBHU62LvBzALwFFQbxsFgNXa1wD1KtabDrI84hCH/B53Ui9jFgHwNu3Ps6E+WBq1v19Sp88gDm9eB3C+9udzAewEcJr29/8H1YEBgCTU+QbGGDt48ohDHKsNegdUZ+YjMDIIsPzZBGPsFAAfg3pv+xUAbmeM+cdF7fiQA3Ai5/wMzvk7AdwO4B7O+Y84578H8ApjrFN77WUA1jDGVgL4KYDLGWMrtb9PB/CY9udVABYe5N/jYHExgP/lnJ8P1am9GMDp2vdOBrBV+3OCc64cfHnEIQ75PS6kXjW99wL4K2PsH1CdlYcA3MIYew+AgTp9BnF4czOAPzLGXgWwBcBPANyh1dMNALhGe90zAO5jjF0D4JsAXpwArcShh9UG/TeAWwB8Xvv+NAfvcRyAvZzzJICVjLHvQK0JztZfbn1hjDUDeBpAljGWA3Ai1GhTP2PsFgBvQQ1y5AFcwDl/CKqdhmanL+Kc/7P295cAfJxzvuPg/yYHlYsBfE378/MAjoV6lmAJgP04TK9hJeoG+T0uhC6nIAiCAMAYmwlgLYA/Afhvzvk+7evXQd1ghQH8F+f8d9rXvwc1A5EH8C3O+R+lr38WANPe5xbt6/8GtUtJEsANnPMntMN1zdAcLgB/4px/VSsp+A3UiGwCwBc4509LWu8EsMR6UEbLfnwVwHsB/APADqgdCjYC+D/OeVZ67ToACsxpWSs3cc7vcDiErkb7t1jCOV8ywVIIghgnDstaLYIgiErhnO8CcDaAowFsZox9gjF2PIB/geqQngT1hPZkxtgMqGU4xwA4E8CPAbXvK4CvQ3Vij4d2QIoxdhGAT0CNwH4AwO+lw3WfgtqZZBGAz2nvcRrUWuQZAK6FetiqKIyxIGPs/QCe1X7uEgBpqN0qPgEgBeAtxthNjLE52o+dArUc4iQA9wC4n3N+kvgPasnREdO/lnP+XXJ4CeLw5qA5vdqD4qUS3/8eY2yJ9t9Gxtg3D5Y2giAIAOCcr+GcvwvARwH8GqrTOgfAJgDroB62nM853w21w8i/Qj0sJxzYEajlOb+AGmH9hPb1S6FGcYc45+uhOpTnat97hHP+Jue8G+phsybO+etQa23/C8AvAUwqI30y1DrmT0CtR10CNUr8z1AjuVmozvkyqKl7cM7TZWpVw9rvQxAEcVhwUJxexlgrgLugnsq3hXP+n5zz87VDBWtgnLImCIKwhTHWzBh7gjH2jHajX4Axdjtj7FXG2Lel19luurWWXk9rf/4fxtgnAIBz/jCAF6CWHvyBc97FOe+CeshrKWPsXAAPAtgO4JPi/TjneahR2vsBvB3ACsaY6BIh15LJf95m/bpWs/4rACsAfKncOGhO+L8B6OacX845PxtqHXwewJWc85s453EAd0Mtr3BCM4Ahh68lCII45DlYkd48gKugts0RD6AntAeTKaLLGDsNquHuPkjaCIJwL9cA+KnWrWA/gKsBeDWnbypjbF6xTbdW//pTGK3LdgO4jjEWZoxNAnACVMf2UsZYF2OsEUY3gzOgttT7M9QornjPYwA8p/33dQBdANoBPAHgGsZYC2Nsgfbzwgm3O1hxFoCnoLYee6/DsXgCwEuMsZcZYy9rPzsTwL9IX3sZavlDURhjlzDGXoF6iccyh59NEARxyDNeN7KZ4JwLZ1d86ZsA7uWc38kYe50xdivnXJx2/CqA/zwYugiCcDfikJhGJ9T6159rf38equP2ANRN90OWH78OajT3Yu3vdwBYDDXymgbwPc75GsbYfwN4Daq9/DnnfCVjbBhqKUE31KhujDF2DOd8sxZRFp0Pbuac9wDoYYz9EWr/1xSAT3HOD5TouncngPugllncB6CTMdbMOS9absA5N122oTnXN3POLyr2MxI+qAfvALUn9q8BPMs573XwswRBEK7goHZvYIwt4Zyfzxh7Amq0IQm1OfhHtIdLC4D7tJo6giAIRzDGxM1aO6F2HFjFGHsXgFM45z/UXrNEK58CY6wdwF+hOrzPiK8fLjDGLoDaKSLFOf+og9f/CECWc/7tcq8lCIJwKwcl0mvDJgAPcc5fYIxdC2BQ+/r7ADw+QZoIgnAhWreDXwK4EmqnBXEbUgOKl3D9EMA3OefZw/SOk60AboNRQlESzvnXx1cOQRDExDNRLct+COBrWt3YJTCux7wYdNkAQRAO0Q6J3QfVgd0F9RrZc7Rvnwg18mvH2wH8SLuI4CTGWMmWYG6Dc76Hc/4453xsorUQBEEcKtDlFARBuBbG2D8B+F+oB8wA4PdQo73PQT1gdqaog5XLGyzvYft1giAI4vCCnF6CIA4rtG4N7wTwIud8/0TrIQiCIA4Nxt3p7ejo4LNmzRrXzyAIgiAIgiCI5cuX93POO+2+N+4H2WbNmoVly6jVI0EQBEEQBDG+MMZ2FfveRB1kIwiCIAiCIIiDBjm9BEEQBEEQxGEPOb0EQRAEQRDEYQ85vRIvb+nHdx9eN9EyqmJrbwxf+stbSOfyEy2lYkaSWVz/h2XoG0tPtJSKySsc/3zvSqzbV/R22EOaHzyxAc+uP1D+hYcgd76yA39cWrR065DmybX78eOnNk60jKpYvXcYX/vrKuQV93X+OTCawuf+uAxjqexES6mYVDaPL/x5OXb2xydaSlV8++9r8Nq2gYmWURW/emErHlyxd6JlVMXf3tqLW5ZsnWgZVfHqtn585+9r6/qe5PRKPLfxAO58dacrHcel2wfw6OoebO9zn0Fcv28UT68/gDd2DJZ/8SHGQCyNB1d047kNvRMtpSr+snQ3Hlm9b6JlVMWDK/fhvjf3TLSMqnh63X78/pWdcGPLyJe29OP+5XvRO5aaaCkV89auITy17gBW73XfJnX3YAKPr9mPF7f0TbSUiskrHH9auhtPru2ZaClVcd+yPfjbW90TLaMqHl3dgz+95s7gwAsbe/HHpbuQzNTPJ6va6WWMTWaMraibkkOAdE4BAPSOui/iKLTvH3Xfg0hsMtyp3b3jDqj694+4VHs27+pxT2TyGEvnJlpKxaSz2np14bzR16sbtWddrN3FNh5Qx96N4w6oY987lobiwszMeDxfa4n03gjjjvvDglTWvQtTaD/gwoWZ0oz5ARr3g0pe4cjkFVeOO6AaxP5YGtm8MtFSKsbN8yaVc/96daWNd7HjKGz8fhcGlAB17N047oA69jmFoz/uvrFPjcMGuyqnlzH2DgBxALa3HTHGrmeMLWOMLevrc08qxtVRAP1B5L6JrUcBXDzubjSIGWnOuDHNns7mwTlcWQvu5nkjIr3utDXuddjTLg4OCBvf60LtgDr2Y6kcEhkXZmZyYoPt3vVaz1Kqip1exlgAwH8A+Eax13DOb+WcL+acL+7stL0U45DEMObuW5hpF0cw9LSdC7WnXDxnhPZkNo/RlPuMecrFjuN4RDAOFqnDYL26c9zdrF04L2nXHYDknBtRdhePPa1XlWoivd8A8CvO+XDdVBwiHB6RXjdqd6/jKMa9P5bRI6duIS3pdeXYu7hE4LBYrzTuB5XDIZuXVzgGYu7Sn81ziESYGx1HN9dTHyo1vRcB+CJjbAmAkxhjt9VNzQSjR+1cmC49HKIAB0ZTrkuzi3EHgD6XGXNZuyvnjYsdmJSLSwQOh8iRO8dd1R5L5xBz2QFIMWcA982blNTNyY2H3PUou8vGHRifTGrFTi/n/DzO+fmc8/MBrOScf6ZuaiYYfSftQgfA3REMdWKnsgpGk+4y5nK01G2Oo0m7y+ZNLq/oaVI3Ho5xdU3vYRA56ou5L83u5sxM2sUb7LSLHXaAuq1YqalPr+b4Hja4+mSvpn0gnnFdn2FXRwEkY+62B5FJu8sMYsrFDgDg9lpw9wYHxLjnFY5+F2dm3Db2bl6vh0tGzG3PVkDOAtdvrdLlFBJy9MVtaXY5CuC2FIzspLttYVKkd2Jwc+QIcPv5AXXs45m86242o/U6MZjWq9u0u9hh55xLXXrcpR0wn/epV59hcnolxI4uk1MwnHCXMZd3o267KUmO9LougnG4RHpdtlFyc+QIMMa+P5ZGzmV9hk3r1W3zxsXOl6u152jOTARu3uQBRmlJTuEYTGTq8p7k9Eqkcwo6GoIA3Dm5de0u68eXzuXRHg0AcOe4A0BHQ9DV2t3mOIrIkRh3N2VmOOf6elW4+w5ApnN53da4bt5IdtKN2gNeDxpDPtcFB+T16sZxBzTtrht3Q/toKlfX63wPBrKtqZfTTk6vRCqbx8z2CAD3OV/u1q6gKexHWzTgQu2qEZnZHnHdTtqk3XXjrhrzme0R113nKx6i+np13bxRXKw9j2ktIfg8zJXag34PuppC7luv0px327inJTvptut8RecJN/sGQnu9Nkvk9GqI6Is+wG5bmDkFXU0hBHweF+6k8wj6PJjcFHLluPu9DFOaQy4cd+NB5LbrfNMWY+6meWN1et04b2a2ufMhms4pCPm9mNTozsxM0OdFV3PIdR1L0i7eYMvr1W3X+aaz7t5gp3P1D+aR06uRySvgHDiq1Z3G3BQFcNnETmUVBP1edDW570GUyuYR8nn16Iub0ux6pLct6rrrfPVIb1sUgLvWa1oad8CFD6JsHi2RAJpCPvc57Nk8Qn4vJrtxk5rNI+R3b3AAUOe8267zTVnWq5uu89UjvUK7i+Z8XuHI5jmmt0bgYfULbJDTqyEeoo0hH5pCPgzF61M0fbBIZdUoQHtDAEN1Kvg+WKSyaqS3LRp057j7PWhrCCCVVUyHfA51hDGf1hoGAAy6aOyFMZ/aEgLgMu3aHJnSrGl326HZnLrB7mgIumrcAREt9aA9GsBg3IXjLrS70MYzJs15F80b4bDrtsZFYy9svDvtpKo9GvCiJVK/OU9Or4ZIlwb9XjRH/BhNuWcnCqj6Q34PmsN+jCbdZcxFyrE57M5xD/pU7QAw6qIWTsKYT2pUDwq4SrvmOE5qUo25m+aNsDXhgBeNIZ+r1quIvoR8XjS5cL2mtEhvkxvtZFbRtWdyiqmrwKFOOqfocwaAqy4hEuOs2xoXzRv9EJ4bbbymXfcN6jRnyOnVEA/RoM+DppAfIy6a2ICqP+jzulK7iPQ2hX2IpXOuauGU1iK9TSHVmLtp7NNa9EWcjnWXMdceRI3u056y2Bo3aTeCAx40hd1na0Sk123jDhiRXsNxdI9+UX7XFPYBcJmdtAQH3KTdiJb60BD0uVK7ul7rp52cXg1hzMWuwk2TQ1E4MnlFj/S6STug9kUW4w64L2oXkiK9bhp74QA0R1yoXXMcm8J+BH0ed2l3sa0R4x7yuTOrJCK9zWE/xtI5V11FLCK9rrQ1WcW1dlKP9LrQ6dXXqwt9AznSW88NNjm9GnL0xW3GXEwOkWYfTeVcd6BKjDvgtgiGGul1p3ZLaYabUo45IwrgtvVaYGtclHJMyWVgYXeVZgDSRk+b8266UU5Eet1YSiXqwN2oXTxfm8N+BHweV2k37KQo6XGRjc9abHydxp2cXg05+uK2EgFDu5o+yisccRc1oVZrej2ujAKISG+TK7Wr4x4NeOH1MHdpz5rrvVylXbY1YXelHOXIkbCTbtlgc85NkV7AZetV1PSGXFgikLXW9LpHeyqbh8/D4PO6b4NtXq/u2qRaI7310k5Or4Yp+hJx10PU0O5OYy4ijm50HK2RXndpV8edMVbXmqmDganey2VOr75eXZhylCNHzWE/cgpHwiUb7JzCoXCY6mLdNvZypNd12v0eNAR88DB3aRfZAQDus5OW9eoq7ZZIb7022OT0aljr7NIuOh0rR3rdmGa3RnrdlD7SI71a9MVN6SMx7gBcl2ZP5xR4PQx+r/tKBPT16qvvqeSDgbVGEHDPehX23HR+wGVj72rtPi88Hua6zhkiOwDA9evVLWsVkMo2tTmfzfO6tAQlp1fDfKJac2BcMkHkSK/bugjk8gpyCndxlFqN9Pq8apmAu7SrkV4ALoyW5vXoi/siGEaktynkRzKbRybnjo4lRvTFfZkZ4yHq0mhpNu/uKLVfREvdtV7lSK/rbI2lptdV2k3dG+o358np1TDX2bkrWmqu6XWXQTTqdlza9kuL9ALuM4jWSK/7tGsOe8iHERdd8GCK9Lqsc4a8XnXH0SVjr0d6fV7Xts4K+b3wez2IuGyDLVpqAu6zNXKk122OY9pyaDaRybvmunlrn16AnN66Yj1RDQAjLklj2NX0usVhlyNHIb8HAa/HVekjEekFoDXrd8e4A4WRXrfMGaAw0juWzkFxSfspa00v4KaskrlGEHBPi0G7SK9bxp1zXhBxdNV6lSK9bruEKJ1TEPC5swwslcsj4PXA42Eu9g3qu17J6dVIZynSOxHIkSPGmPt20jkXRwGkSK+acnTXg0ged86BsbQ79KfllKPLshtuzszIDnvY74Xf656OJXJ9I+DCEgGtpheA6zqWFNb0Zl2zwU6bgjLuym6Yuzdo2uuQVXKV08s5x31v7qnI209kctg7lCj7ulTOLtJb38nx5Nr92DNYXosgr3Bs64uVfZ0c6W0M+sBY/R32pdsHsLZ7pKKf2do7VvY18oMIUBdmvbVv6BnFK1v7K/qZHf3xsmkgtQXS+EZfekaSeGx1T0U/s284iZgDB1CO9Art9Ww/FU/ncPcbuyt6z/5Y2tH98HKkdzw2qYrC8efXd1V0mHUslUXPSLLs61JZBX4vg1c71APU39Y8tLIbvaMpx69P5/LYNRAv+zq7SG+9tf9jcx+2HChvOwScc0e2Ro70qh1L6u84rtwzjGU7Byv6ma29sbJOlJymBsanRGBnfxzPrj9Q0c/sGUw4WiNpS6S33tqH4hk8sHxvRT9zYDTlyIkyd2/wQ+FALFO/DXY2r+CPS3dVdBPpcCKD3rHy6zudM9t4oP7r9a/L9lTkjCYzeUd+kAhE1rsGvyqnlzHWzBh7gjH2DGPsQcZYoGYlDtg7lMS/P7AaD6/c5/hnfvuP7Xj/r14p+zpr7QtQ/9TXV+5ZgTte2eH49Y+t6cG7fvYi+mPpkq+TI70ej2rM650++t4j6/F/T21y/Pq13SO46Kcv4q3dQyVfJ0eOgPFJH938wlZ8/YHVjl8/kszi4p+9iL+v6C75ukze2IkC4+P03v3GHnzp7rcqcr4+9JvXcPPzW8u+Lp1TTA+iTF7R/z3qwbMbDuCbf1uDDT3OHZh/vnclvuHg30rVPn7GfH3PKL714Fo8u8G5E/CTpzfj2tteL/s6ax04UF+HPZHJ4av3rMTdb+xx/DP3vbkHF//8xbLzTHYcG0Pjs8H+5gOr8UsH81fw6rYBXPTTF8sGCOSaXmB81uuNT23Cdx9Z5/j13cNJvPNn/8BzG3tLvk4+cwKIUqr62vjfv7IDX757heNNqqJwvPsXL+HOV3eWfa050lv/cX9k9T78619XYd9w+U2n4DN3LcP3H19f9nVpS6QXqO+cf337IL7z97VYut35Zum7D6/DP/3prbKvUzt+GDYeqG85Us9IEv92/2r8fWXpZ6XMbS9tx+U3v1z2dbpvYCqlmrhI7zUAfso5fyeA/QAuKfXiD//mNXzzb2tqbgEmole9Y6WdQJm9Q0n0xzJlr5tM5YwG1HraLpHFv963Cp/9wzJH0adSZHIKMjmlQu0J5BWOoTKfLUd6ASN9dNNzW/Ch37yKnf3lIzjliKWzFUWO9g6pxqd3tPTva430iijAQyu7cfHPXsTyXaWdZifEUjn0jqUdG/O+sRQy+fL/VilL9EVEjlbuGcbbf/wCnlhTWYTWjlgqB86BPofzJq9w7BtJOooCpKTDJSJ9tPnAGN5x4xLc/vKOmqO+xnqtbN44WSPWml4A6IulcfkvX8b/PLq+5sMaY9qDodz8ldk7lHCovTDlOJrM4rN/WIav3L2i5lvCqh33VFYp+1CR16vHw9AQVG3N/zy6Htfe9rqjSHc5xtK5CrWrUaNya0R22AGjHOmPS3fh8l++jPX7RqtUbDCWzlU0Z3qGk+C8/L9Vga3RMmIvbenDO25cghc391UvWmMsnUMym3eUJQLUTabT39favSGdU7ChZxRv//ELuO9N55uzYujrtcLnq5PXmyK9mq3ZO5TExT97ET97ZnPNV1nH0uqaq9xOOrDxubzp+QSo/25X3/oavvHAaiRr7LEdS1Vna4YT2bIda1LZPBgD/F6GRkn7v9+/Cp+5600MlAkGFqMqp5dzfgvn/Bntr50Aim5Ts3kFb+wcxN1v7MbVty6tKIRvJaGlFMpFPmWGE6rDGC+TjhA9EAEg4PMg7PdiOJnF42t68Mz6A7j8ly/r71UNuvYKFuWwljIoZ4TkSC9gOI5PrduPN3cO4fKbX8bmCtKFdiTSefTHnP/++riX1W55EGmO47MberHpwBiuvvU1vLCpdBSkHIlMDpmc4rjmc0gb9/LajStZAXXc45k8nttwALsGEvinP7+FP7y2s3rhqHzOqw28y2sHRD2y2XF8dv0BbO+P478fXY/vPVI+ClKKRFodn0rmzVAi41C73L1B1b5i1xDWdI/gtpd34FN3vlmT016NrRlKZBFPl78C3C7luH80hWc3HMDDq/bhfb96paaHkTHulWgX69VZpNeUmUlm8cTa/Xh5az8uu+llR+VkxeBcveyisjnjcL1aIr0i4vj0uv1Y0z2CK379SsWlCVYS6RwG4hnHNZ+V2ho54jiSzOK5Db3Y3h/HJ37/RtnMVDkqXa9DDm18XuHI5nlBduOJNT3YNZDAvz+wGj97ZnO1sgFU/nxVFI6RZNaRrTF3b1A3qa9u7cemA2P4xXNbcMO9K6sTrRGvcr2WW6uA2a8R4771wBiWbh/EPW/uwVW3vlaTTyZufu0fq8zGA858g5B2eZLXw9AY9GE4kcXja/bj2Q29uOyXL1cVjKypppcxdhaAVs75UsvXr2eMLWOMLTvQr0bqLjp2ElbuGcb+CqKFVsQ/stOoF2AMcKLMBJF3RIA6QdbvG0Uym8eFCyaheziJ1Xsrq2mVEZOjr5KJrf2DlrvxyBrpbQ77MZTIYGtvDBcumISxVK7imlYr8UwOg/G0412tMOaJMpsNu0jvaDKLLQfGcPrsNoR8XjxXQYrZjkrnjdNxL6yzUw3isp1DmN4axjGTG/Dk2v1VaRbo88ap9oQz7UBhGyEAeHPnEDwMOH9+J55YW1ukWmw0K4lSjySzjrSbIr0RQzug2pqXtvTXdBV3peMOqGOvcJQtEZEPl4iuJW/tGgbnwIULJmF7XxxbHNSoFtde2bir2p07jowBAa/h9O4bSaJ7OIkLF0zCQDyDN2twHNM5BXmFV2Xjy/17WzfYoovAlgMxnD+/E5mcgiWbaouYJjJ5NTvnMEDidLNhjfQ2h/2IpXPYuH8UC7oaMaUphKfX12prKps3+pwpF1DSgwPmDfabO4fQEPTh9NlttdvJdGXP19FUFgovP+5AYZ9ewGxrnljTU5cNdiVzfjjh0GHPFZ59ENovXDAJq/eOYN9w9T5ZQtNQiV8z7HDepLJGdgBQ9W/aP4ZYOocLF0xCz0gKq/YMV6y5aqeXMdYG4JcAPmX9Huf8Vs75Ys754mC0AQBwwYJJAJxNsmIkqngQOY6WSjsiQN3RrdQG9B3HCu3V18Ika3gQOY30ytHSjT1jSOcUadyr155X1ANbCgcG4s70i0hvrIrI0Ugyi+19cZw8owUtUX9NcwYAktnK5k3lEXYjcgSoh1kWdDVhSnO4pnEHpHnj0KgY4176cxWFI5M3d28AVO2z2qOY09FQ+7hXuF5HtSi1k/RqJlcYwVi5Zxg+D8O58zoB1Gm9VmHMncwbEfUC1LG32hqnKWY7klVssCvJzAR96kEwQNW+ao8aDDC0Vz9vhPaRZFZfX+UYjjtz2OUb2QB1k9ozksT+0RTOmN2OaNBX07gDkgNT4XqtNNIr1uuqPSM4flozOptCNY07UPl6daxd3Apmcb5W7hnGvMkNmN4arnncK9Xu1GEHCrs3AKr25rAfJ89oRU7hNZ2FqNSv4ZxjOJlFOqeUjdLKfk3I70XA56mrranGJ3OcVZLqwAF13tRDe7UH2QIA7gPwTc75rlKvTWcVTGoMYlpLuGqRgmp2REbkq4xBtIn0CmfppKNaANSmXfwDj6Vyjmubh51qt4kCCO3HT2tGwOup7UEk6a084lh5pFfh6iGx+ZMbEQ3U/iASRrn+2gvHHVDHa35XAxrq8BCtPEqtRdgdbjaskd5kNo9jJjeiIehFPFM+VV+KeIUOgNNxB8yR3mjAC6+HIZnNY05nFC1a5Lce69XpuCsKN9arg6idHMEQ6zXg9WDhlCbT51eDHKV2+u9nZGbKaTdKMwCzrTn5qFb182sZd+nfvt5p9nSucL2KNSzWa62b1MozM8L5qjzSC2i2RqzXuml3FvlzrN2mDAyQtfscOZ+lqDxK7czxAuwjvbJ29X1qmfOVRqlzesbVydjb+TXt0QBmtEW096h9vVaVVXLik5nspK8utqbaSO+nAZwK4FuMsSWMsauKvTClP0TrOzmsxnzj/tGCNhh5Rd0RAc4ivUG/OfoCAFOaQ5jSXLvDLv8DWyfInsEENu4vPEQx6DhamjdHX7SFCQDzJjUgGvTqxfLVkEgX1z4Yz9geNnMepTZHekXNFAB93tRqzIvtRtO5vO0BkErGHSiM9AKqdnXc6xQ5smjnnOOFjb0F5SaDDiO91jpws/YGRIM+cO6sTKKo9nTxh+hr2wYKNIo5k83zslE+ucew2n5KnTfztI0SUJutKbXBXrN3BAcsZVoiXQpUEenVxn5OZ1R/qNZjvaaySoGW7X0x2y4HoqTHyXoNmVKO6lgHfR7M72qEh9U67sU32L2jKazeO1zwM3q6tOxmwz5aCgDzJjUiWqPzlc0r+uEcq/ZYOofXtg0U/IwY94ojvbKNn9ygBgdqPJVfLEqtKKqtsT5zHWvPWmx8yLDx8yZr4+6gFr609uKbjRc39xXYE6dRarUtpRHpjQZ88DChXbWT6vvUYieL25rlu4YK6lblg+1Oxt6UwdbtpKG9lnkjxr0/li6oY9+0f6zAJ+OcV5QhsGbEAKCzMYhprdX7ZNUeZPs157yVc36+9t+9xV6bzinmAa7FIGo/a3co6YZ7VuIHT2wwfU2kS9WfdeY4CsTDZ57mvAA1GnPp860F6z98ciO+evfKgp8RxjzhxGG30T6tJYxo0KcZldojR0Bh9OXOV3bgI79bWuB8OY16pW0ivQDAGHB0Z0PNKUfOuf4gs477k2v34+N3vFHQn3Q47mzci0VfAOkhWmPKMS4ZFZl1+0Zx3Z1vFjjtlWcHjKt8de3agwioz0bPOmfGUllcc9tS3PPGblvtgJNoaWHEEQCOmdRYF2Muxt3uUNL1f1yGnz+7xfS1IalPpZOxt0Z6AZiCA7VkZkqt1/94aB2++bc1pq+JdKkz7fbjPndSA7wehmjAp5+kr0q7NN+sh5JufmErPnXnsoKfcZohsOt1CwCRgFe3lbVoT2SK2/gHlu/FR29bWtCJp+Kskr/Q1oh5U6+skvVQ0qvbBnDdnW9ihaV+0un5AT3Sa7HxqnY1wq5udGs4UJW2t/Hdw0l8/I438Mgq8/kEkRFLZvMlz6nkFA6FG3PGI/XWFhkxABirYZNq2HjzuHPOce1tr+N3L203a5ftZBUZbEN7HWy89rM57TyGzL/+dSX++1HzYeixdA45EaV2cs7K1k42IBrwVq193C+nUDg3pQHqUT8CFO6KhhIZdFsKsuXJ4ax7g7loGgDmT25A0Kfe3lPLgyhRokRgKJ4p6C8op0udRAHM9cia9q5GAKjZICZKRKkHExlkckpBra/YnZZr4l0Y6VW1z2yLIBzw1qw9nVP0jY9dlBpAQSH/UMXRUrMx93oY5nRG9bRdLRGMYrVqQnu3Zd4MOYx6WSO9Pq9HX6Pzu+q7Xq3aR5JqVNQ67nJEo9KIY7M+5xvqol2Mu92hpEGb9Sq/ptJIb7O0XqN1yIglS61XG+1yutRJDb7tuE9WbU20xsyM3LXCGnEcjGfQH0sXRO2crtdULg+vh8HvNTuO8yY3au3XaisRSJZ4Pg3GM+AcBQe5Kz23Ye2A0Bj0YUpzqOYotarfPtIrskeFc955FhWwzyqpJWy1B5X0cxuxwmcrYKfdmeNozQ4AZsexHpFeMe6D8Yyp1WI6pyCZzRdoH5Y22GXXqyXSa699fNbrUDyLfZYWhiKg5ORzrZFeWbvP60HI7zmo5Q0VMa9O5Q2lnK94Ol8QGZCjL452FTYpx3mTDcextkivpD1m1Z5TeyRKE2gsldPTpU7qvUynHKUURl20lzDmxWofnUapC25kC9V33ONlxt3u68OO6xsL+/QCwMz2CEJ+1WGvtUSgWF1ssTplsVHKSKnW0trNqS+fh2FWe7RO69X+UFKxk9bDpmhp8THL5RXkFF50vTZo87+mWrUi8yanXeBRbNzLaQdKrNdJDYgEvGA1lgjES63XTK6g1tccYa8s0ltgJ0O1OV8ltevRPEOvmi51tl6tGTE9YjdJtpO1r9VS2ovNG8e2xlIGNm9yAxhj6rjXMGcUheuBmYq1V2jj/V4PIgH1woHOxiAaNLtZ09gX0Vjs60MO16u14wdg2PljTOUN9ZnzA7HCzXNJ7Y7Wq82cr1ekt8R6jaVzZca9sppeWTsANAT9VQUiD4rTOx6TQx5MkcIuZcyLfW4mpyCVzRdEeusdwSg3OaxfH3KgPa9wxNO54pGjemkv4TjaXRgip0uLGTLOOUZT6glUj9aAurj2GiLsJcdd/Z710g0nB2NU7eYoQMjvQcDrMWkv9z5l9UubCnluF7uoZShePs0+lspKEQyzUZnTGUXA56lPeYOcqrYx5sXGvdTnJjN5fT5YtQd8Hsxsi+jlSDVlZorMG/HZpca9mPZ0Lq/amhKRXsYYGmo8vGmuwTePsWovFNOtTHJwoFhmJpdXkMjkSkbYAWjlSLWMe+nABmCeN3K6tNiYKQpX57wlI9ZsyYjVWkoll+QUbFIzRdarg2ipydZYIr1yNs9JLXwxUrl80YxYvJitkVrFFetLLGw8gIJ5M3+yNt+D1aeqBWK9JjJ5k90xxt0+wl7qc+PpnP5val2vHQ0BtDcE65QRs5/zxce9vHZhZ+R+5kI7YC4RqO35aq+dc9U3sV4MZrbx9p+bySlIZvKmlppm7WLOV5eZ8ZV/SW1EAl79No1auwgk0jk0htS6K3mAExl1wWbyCkaSWbRE1FuRTZHeIsb8Px5ai+198YJI7zlzO3DZoilYMKVOJQLazzYGfcWjpbEUZrRHNO1yaYb9mN3x8g787qXtOHZKk2lHdOL0Flx07GS9dVND0FdTw3hhUBpDPtuHKGCe8ObTpfZj9vzGXnzhz2/h4uO6ENQaUAPqwcHLT5yKd58wRdNudBEQr6kE8fmqdmeR3nKnS7f1xfCun72IK06eBsCI9DLG8LGzZuLso9s17YZBnFSxcu1gTF7R53wsndPXkpMIRjyTR0vE/J6JTA5n/eB5vPuELk27Mec/eOp0/TBnQx3SdolM3rReRQeXcuMudNrx3ptfxskzWgq0v+eEKZjZFjGVadTaRcDO1sT0VKTas9qrnWpxEn356t0rkee8INJ7/oJJ6B5O4ahW9R+rHhvssN+LTF4pukntG0vrD5EhB7XUP3t2M55Yux8tYT8iAeOxcdqsNrxr4WQsntUGoPoHka49Ldua8sGBYQebvAdXdOO7D6/D2+Z2mKJeR3c24OLjJuOdCydr2muNUhe3NTGbjJh8qKfYuK/cM4wrf/0q3nfSVABGxDHs9+Lq047C+05SbZDswMjrwrF2adzFoSSPNreLRRzlzEwym9c3yoL+WBpn//B5vF9ol3RdfdoMzGhX7YEeHKgxMyOvV2PTXiwTWXrOc85xwY1LcP589Rkqr9f3njQVZ42ZbXytc17XHksBaNa0l46wA8Wj1J/8/Rs4qjVi6jwBAO9cOBmcQ/eRQn5PjeOet7WT6Zyib0aHEhl0NAQ17eXX6/ceWYcNPaMFkd63zW3He06YguOmqh1uqrWT4+70Ht3ZoP85WqNBTGTymNocxvZszFSwLr9n71jacHq1eh7Gik+Orb0xrNgzjMaQz7QTnd/ViJs/eoqkvTaDmMjm4fcyTG0JFxTb2zkw4kHEWPGH6NbeGHrH0lD4CGa1R/Wvt0YDuO0TiyXt3rpES2e2RwqK7e20DyecjXs6p+DVbf2mcfd5PfjlR06WtBslAlajWqn2DT1jJmOuax8tfBAxpqYUZcdGsKMvjrzC9Zvi5J30dy5baNKufk51Yy9rX9s9iv5YxnB6i7S5GdK0c24/bw6MphFL5/D8RqHdGPvPnDtH0l6Hw5uZvKHdJoLRN1pozIV2uzFTFI5tfTF9bcja333CFH2jFPZ769JFwBj3Qu0KBwZiaUxqCgEwj3uxTerWvhj2j6S0/sjGnDllRitOmdGq/70e6zUa9KHJYz6UlMsrepq8byyNuVpaX7aTxWzc1t4YtvfF0dEQ0Fs4AsDUljBu/bhkawI+DMRq2WCrn6/amvLRUtlOFhuzrX0xjKVzWLZrUF8/ABAOePHbj8l2sj71yDPbIwX16kbUzvh6LJ1DNs/Ljnte4fqBVRFxZIzhh1cuMmkXn9MWDdSkfW33KEaSWbRq71Nsgz0Yl+d8rsA+7xlMIJNTbG3NVy+aV6C9phr8bB7zuxr19TqrI2rSbpeZkbVbGdWurhfaZYf9w4uPqq92k52UM7xGeZjcQcI67nZs7Y1ja6/apUXuSnXuvE49GAbUHsxLZnOY3BRCJpco6pP1jaV1p3cw7mC99sb0PshyhH3upEb86hqzT3ZIHmSTqdWoqMbci46GoDn6YhlgwVAiA5+HoS0SKDo4/TE1YjOcyJoeRHbaa2rtkc4hEvChszFYmAawM+ZaBGNyY6ikdvX/mfLa65B+mdkWdViaUV/tQPUOjNjFz2yPFhxK0rVLi1WkSyc3qs6MnVGRtQNmY27WXtvJXsMBUA243ZzvszkYI7TbjX2hdvuxr1faTtceK9RurWMfSmSMcbf5XHHjWTntjLGa+zsnMjl0NgQR9nuL2ppey5xviwTg87Cic7U/pm44MjlFb9RvR0PQ5/jK7GLao0GvamvkB5E01rLzJa/X4toz+v+DJdZr7YdmtfXaFnVUxy7Wc0ntY8acD5YZ91pKBOLSerUeSrKNUlvG3e7Aq7xeA16PvmG30w6g6u4TcautMa3XwpIeUUttrNfCMZPnDICiEehao6WZnIJsntvaSXnOyONbztY4tvF1KBGIZ3KY2VY47ubyMPO8KaU9r3AMxtNl7SRQu18TT+cRDXgL/Bp5PHotATHGgI6GYEk7qXDVLhUbd6D6zMxBdXprNYhiN9nRYDHm6eLGvCXiR0PIVzRaKheOlzaItfVcjWfUydHREDBpT2bz+oE1O2M+rTVcNFraH3eqvbYuAvG0EQUodijJPO6S9prHvTbnSzfmWiNusxMgaksL06WiD6Bd6mvA0naovDGv8iEqxl1otzPmUs9qEaXWtdvMmwGLI1Fs7GvdbCgKRyKT1xug22m3fn04kZW0F35u4bgXnzc1b7DTarS0ozHgUHsGLRE/okGf7bhn84optVfKcay9Bj+PSMDnODgwnMjAw4Cu5lBRWyPPm/Ec93gmh6DPg8lNoaIb7F4bx7GUnZTnTclxr9GBSVjWq2zj7CKOsp0sdn11JeMOVF8ikLDaSbsNtqWkMJNX9PVq929eYGuKBgdqDGyUsPFCu7WOXbY1dpmZgZgzG693EaglC5zJozXqLyiLKb7BzmBqS/HNxrAWHDC0l5g3gVoDkTnD1piCR4atswbEmsPq71pszEzrtUSpTrXnfQ56pLfWNEDYX7irKGXMWyIBRAL2hytS2bwpolJyRxSo7UBVMpNHJGhEeoWjYprYo2ZjLh5E5SIYZbXX2EUgmcmBMWC6VnPYb2PMTRNbm7TTW8NFDznIDruTSG+180ZO21l16vVescIH0fQSza/l9/B7WUH5g1V7tUZFaJ+lRzDMqVFAvcjBuMs8j2yel9ZuMebFxl50Eah23EVvzpawH81hv9lxNLW5MX6nwXhG0m4XObI+REvNm9o2qYlMHpGAF50FG+wiWaV4Fq2RAKIB+8+1NpgfT8cxmc2p0ZcGa/SleEZMPIiKZ2acr9dabXxEixzJh5KspRmCQcnWFPtc2fkqFWGvtb+zXJph1al3nrDJiJVar/K4l9soFXsPZ9qttqZQ+0A8rV97a7WTpaKlgqJZpUBtUWqhfXprBB5WfoPNOcdgIlNSu9VhLxdxrK2/s30WuPh6zaItGkAkYF8uai1BLLVe65GZ0bNKRSO95oCYaiftbZw1OFB63L1VjftBj/TWGgWIBn0FxryY46gOsB8NQW/JyJE4H1Uy4lhjS5h4Jqcbc/mmJNnAWp2v1kgAjUVC+JxzDMTTzrTX6HzFM3lE/F5MalTrcmTjEbMrzRDRF+3gknyNsaB/rDLtNUd67UoEUqrOwXhGb++lR19aSkccDe3FDUpjnbRPbQnD62HmCIbNvJE3G0W1O4z01tpFQBg9eaMnkA2VWK8iXdrVHIKH2WsXxtzZeq2unY2uv8iDyKTdYsxbIgEt0lvcAdC1l3gQNdaaEUvnEdZsjXxTUvEyMLV+Mxrw2WY2Utk8Yumco3FvDNVYIqBFqTsttkZ+iMqbP5EuVaPUxR12R+MeqnW9GqVUgHlDZx+lttiaIhs9p+MO1GDjtc+eYRscUN+Tc2OTMWxx2O0CKvK4l9JvnB+o9uyDqq8x5ENbtIRvoM2bZDaPTE4pOFhr1m5Zr2UjjtWNe15RD7ZGbDapxSK9w5KtsY9SW7WX8WtqjFKHK3DYhxNZtEb86rkFG+2DBT5ZaYf9kO3TK6i9A4IaBWiJ+vWWWIAxwB5mcRzjWT3SW2o3t2h6C4DyO6JaSgR07dohO+vVmdYd6pCWLo0UiTAnMnmksoquvVydHVBLFCCHSNCH1qhf0270luS8ULtIl05pLl53NBBPV6S91pSjMHDyLjKezutXSorLNYwIhmr87cZsIJbGcVOb4PWwkjvReqXtGkI+tIT9Zu2ZnK5djH2hdvu0XWvEr5cdjFeaXWiPBrxojfgxnDRnB3Tt2hoU6VIRBSg27oDT9Vr9oVnOuR7BaI0ELHNGsjWW9doa8SNSpGWXSJeeKLSPZ2lGJodowIfWSAA5xTgzUNxOqhvsSJHouAgOOBn3mksEtHrk1ohma8Q18pli466mS5tCfltnm3OO/phha5xEemspEfB6GLq0w43mSwTUOR9L5/S1YUSpS9majDTu429rJjeF4PWwoutVOF+OtMczmNkWQXPYD8bU7k121FoiIOaamDfWyxsK7aS5hK1UPfIJ09ROCiXHvoYSAcNOqutVHncxpowVZjdaI35Ei0V64xZbU9bG19Yf2bDx2YIMtnW9DsZLR3r7C2x86Tlf7kY9Ow5yeUNtp5JFpDfi9yGTU6RbhNTBm9Yatn0QNRTZEYkBvnCB2lCqXMpR4fZRS8faAz5EtIeC6JMqazdFjrR0qdyyqxbtQG21pdGAF2G/z6Q9LmmXU5FGutTcaUDAOcdALIMzZ7chEvCW0V5bFwFhSMXpUfnfL57O6YZPN4gOanr7Y2r7rfmTG0vuRGu9aEA35gEvwgGvSXssndc1inljjbDb1VP3x9Jobwhi0XTVmJcb+1rrkSMBH8IBH5JZRfpeDl3aw9XqsLeKutgijqPXw/D2eR3ltdfwIEprtkXVbh53MZentYZ1x5FzrkdLG4LeouMOSOt1XB9EeUSC6pwBjDkvr1dzRiyr20nbKPVYNbamhqySNu6AUeIja5fr2I10qfp667yJZ9RepW8/phMeNr4lAnEtsBGxjLsozRDrVZzQF+t1ilafWSxDsGByI6a1hEtHvQK1XV8t5nU06EXE70UyY16vBXbSQUasXzu1v2h6M4I+T8mWk7UExISNj2jP1/I2XtXeHg0i5PcUyeal0Rrx611VxuvwpoiQR4JeW+1hvxftUeNcQVKbzyWzShWs11rPKiW09RoJ+JBXOLJ5ccWw7NfYR6mLZQeca69uk+qa7g0iDRD2exEOqLKtxnxWe1QfYJEubXVQ+3LRsZNxwrRmHKft6oppB6qv9xI1vWFt8SQyhdr7Yxk9FSnSpRGtHtfqbOs70enNOO+YTr13qb32WrsImB9EQntM0g4YUYAhadzl31Ewkswip3BMagrhilOm4YzZbUU/u9YodTKj3kgT8nvgYcZDVHTN0LVrToBIl05rKd69YSCm9h18/8lT9Z68doguAtWexE/qBlGdN3Kng3g6V1B/JyLwU1tCRZ1tVXsAly2aijNmt5U1KlWPe1Y8iLwI+z2mq3FFv+H2aEAad3Vu6hHHIg5AWzSAi4/vwoKuRj3KVHftYtwD3oJxj6Vz8HkYprUYjqNIl7bq5wfsxx0ALjtxKhZ0NeJY7VIBe+1qj91qSwSS2TyiAcPWJPX1atRtypFe+eyDnbMtsiBnH92O02a16hEke+21rtecPu7q75Izvd+s9qipjl2kSyNFPlc4ADPbIrhs0VQsntmKYtRaBibqkUNWh91SLys2qcNacEDc8GXVrigcg/EMOhoDuOKUaTirhK3RL2Sp+vlkRBxDAa8+7qquvI2tsdYj28+bjoYgLj9xqqlNlr3+6n0Deb2GbNbrlOYwAj5Pgfa2aPGsUv+YauMvPb4LJ0xrRnuJNnC1lAgkZO0Bq/a8cXBfD2xkymofiKfh8zC876RpOGZyg96a0I5ooPruDWpGTM3MhApsjeTXWEuptPKGUtm8C4+dhEXTm3G8A5+s0nkz7n16ZeQSgUovGhBOXzToRVjb1SYzeVNdx6z2KFbvHQFgTpems0rJUPqsjgge+fI5ZbQbt8ZUc9FAPJNDxG8TfdEWy5yOKF7a0o9BrZHzcCKLRdP9piit3BReaO9sCOIPnzq9jPZa+8XmbCMY4v2E9r6xNGZ3RDGsRV+KPUSEw97REMCnzzmh5GfXHjlSswOMMUQCPl276Jqha48ZDrspSm0Zs1xewWAig/aGIK4/7+iyn19Lb2o9guG3jwJ0NYUQ8nt050tEMNqiQTXSWSS7cezUJlxyfBcuOb6rjPbqH0RyylEed/F7RYNe+LxBady1SG9UnTf20dIM2qMBHDe1GU/ecN74aZccgHhAbWGXzSvwe9W73qNBHyY1hrBq77CmXTjsIlpqP+4Bnwez2iOOtAPqGFZ30YD9ehU17GLOZ3IKAj4PhhIZtGlRanF9dUDaDInI5OSmEP76+bMdaq9+3kxtCei2TkQcxfvJ67U1GsBQIoOuppBua6xjLxz29oYAbpL6f4+Ldi2bZ91sFGiXgwPanLHTLoID7dEgPnXO7JKf7fN6EPTVXiIQFrbG5HxlMVvT3mtxvqaWzCplcNqsAD68+ChTb1s7asnMxHXHUY30Wg9aT24KmeplC7JKdnWx8TTaGwI4Y057Wd8gGvQh3l9tRkyKUtsENhqCXkySOpmYtXsLOtoA6nptiwYwoz2Cp//57WW1ixKBYgeyi5HOKVC42u9atjXN8OsO7eyOKFbsHgagZoiT2bze/7lURmxGWwQPf6n8uAOVr9eDHumttkQgIU0OuwhGNODF5Kag3sh5RKsFaw4bRdPWEoGBWEZb5OV9/2ig9trSSNBro11z2DvMO+mRpOp8RYtES0XkqL2hfCPyuqQcg77iu7kOcwRDaBfRF6shFhO7PRos+9m1lgiIWmpArW2yRqlnWiK9uvYi4z6UyIJz1WF3Qi2pajn1JWsX+oXzJRzHkaSqVegvttHrcNi8vpaT+Akp5VgYfclr2oOmOWPWbu84ijIVJ9rrNe7y12LpHBqE9lE1zT6SsGq3dwA6ogFHm/1a1msuryCdU9Rxt2Rm9Iijtl4H4mmksurZgGbppjVryrRfcxydjH3tXQTUDZGRETPXI+u2psh6tX5u35jYYJfXXmuJQCKj2ni/1wO/lyFhzUR2mDNi5bTLDrsTakuzq6l0j4chLNkaUZrRFg2gSWqpNZLMolF7JgR8noLMTC6vYEgLDoy7du3nolpJjzx/9U1qU9A07oCxXot1zXCuvfoSATHOUS2TmsgaforQ3tlQqL0pLM4P2Ed6Kxl3oLo6djGv5Y2evF5Dfg+6mkN6HfuoPO5ayam1s9NALIOAz7hVs7T26q6bP+gH2YDqDGJcSgMURhxzaAgZJ377Y2npoetFNKjWm/SOpXHvm7v19xyIpdHR6NCg1HCyV6TSo1rti1U7oO6IANXpVRSOZFaN7IqHyEgyiz+8tlNveD5QgeNYaxeBhFasro97prh29fWqoylPyvuW7dEPPwiH3cnYG10Eqq+lFrojAa9Uj6z+vzXqR2vEr5+0Fu1jxL9TPJPD0+v2Y0d/XNVegQMA1HYSP66l0gNej0m7uNe8wdIZIaH1OPV6mF7H/vr2AazYPQRAbeI+mspVpL3WyJFYr9YIRmPIol16vcgIbdo/pt96B4h0qbP12hjyVV0iYERfjA2xXMcuxj2ZzSOeyRu2JujTtR8YTeHvK7rN2hudjztQ3XpNSBmxiPYgSkkOu8/D9LKQvrG0KTUs7HN/LIM/Lt2lP5AGYhm9rrys9lBtwYG4ViIgPss4+6D+X7c1+npVHU352fLn13fp/4aVrNeazw+kc4ho5x7kshjx7zijLWKqYxcXFumR3nQOj6zah33DSQBGRqzTqQNTQ4ehuHZwE4Cpjl08d3VbE5NsfNC4sjyRzuPFzX1Yv28UgBEc6HTqsIeq36TqvoHfh7Dfp7e2A9R502Dp+GRdr4lMDqv3DuO1bQP6z/XH0o7HvbYotfpzYW3Oc6lfc0xy2EUXFmEnowEfGrRuK7sHEnhiTY+kPePYTjbU0PVDLs2wZrDlcQfU6LNcNy58gwNjKdzzxm7d0e+PZdDZEHQUHGgIimzsIRzp1Q1TFTUkcuTIuquIZYyoF6DupEVaLBLw6VHaO17Zga8/sAbdklFx4jTK2quZHCINEDFFMMzGfKZUFyt6nEYCXl3742t68B8PrcPS7QOa9jSaQj5TGrIYtZ/sVR1wv9cDn4cVlGZMb43A72X6blR12A2HYd2+Efz7/avx8ErVCdAjGA7HXo041laPDECLYJgjR9GAOm/k+sxIwAuvFvEYSWbxpb+swB0v7wBgpHpL1XhZtdc27l4wxrQIhjruqaw6n4xoqVk7oM61eDqHb/19LW58ehMAOXJUwbhX2zszKx1k86sPUVMEQxt3UceelF4vuq389JlN+OYDa/T3HKgg+lJLFwHDEfTp5weMGnzVOZjUpOroHU1J2tU5n8oquOOVHbjh3pW6w9MfS1c0Z9TPqnzszdoLzw+IOaNqT5u1aw+ivy7bg+/8fS3WaQ6MOPxYifZq12vSepDNEhyY09Gga5dfL9b4q9v68a0H1+KZ9QcAGBtsJ1fzii4C1dexG45gWNroiTnYGPKjoyFgap0lj3vPSApfvnsF7n5DDczoGbGD4HwlLXbSGtgQz1eznVRfL7Ib/3LfKvzqha3Vaa+pBl92HD0FZWAN2nrVx13zDcJ+r95t5fuPbcD3HlkHAEjn8hhL5Spar4lM5V0EVC1S2aa1LCZjZJWyeY7hZLZgvcbTOfzmxW346j0rJcexsowYUJvTGw3al/SoDrvwyVL698J+Y73e+cpOfONva7B3SPhkaceZDf2sUoXPqINe3gBU9yBKyJOjoFZNnRx6n8VUTv9e2O/VP1fUlogDP1VNjioiX9YUhp325rB2mCGVNSZHwKv/w67YI7SrD5P+eMZx5KjmEgEt5Sg0id9HTLbGkLpjFg5SMpu3H3ctvSF69Dq9I76WLgKJggiGYtIu5o0wuOICFPVzfVi3bxSZvKJrr8pxrGncxYPIp88LcSCxIaRpT9loD/gwnMhgR39cnzMDUi21U+3Vl/OYU47yjVOxlPp7NYbUDExSq/VSf0+v3n9y84GY3sInkckhkckfFGMel9er3zg/AKhXJ0eDPjQGjcNHhjGX1qs250U6siKHvZaMmDTuBTW9aYudTBt2MiSvV2FrkkZmxnHkqIYSASMjZhccUH+vSU1B/dIUztW5E/IbkV47G98c9jsKDgA1dhHQNnMATHXsYgMQDXrRGDLqHZPZPEIBL4I+L/xeVmDjKylhq4d2OSNm3WwU2Elt3MX39g4l0R9Lm+YM4DwjVkuJQDyTR8DrQcDnQSRgdDTI5RX1UGfQVzDuAT0jpjqOmw+MFdpJh8/XepUIFNbgi/Xq1/8ur1eRVdq8fwyZvKKvlQHt7IMz7dWVCABy14wi2XfJ1oxJtiYsZZUK5nzcuU9WbSDyoLcsA2oz5nY1vcLYyJENY4A9etRnjXbIbTQpUl8VGPNg9bfGCO0ihaFqNyKO8gMqITkA8oNI154SCzONDoeR0lq7CMQzeV132O8taFkWDfo0Y6MdEsuoxjxSZNz74xm0RQKOC+drN+ZyBMMS6Q36TI58Mqvoxjwa9EraNYe90pRjLdrlcZciGMIRbdAOiQkjLx6i4vfa0DOGvML1OVNp9EU+2FSNdsaAkM9wYFJatFdEMCLyetXGP+hT1+tIMotdA3GksmqJQjUOAFBliYCe/pQ32Ma8KdBear1qvStFx4/x12444NYafEO7cXDK5LAHrNqlKLVjh736EoFUVgHnatrZ62EI+Dwmh93nYQj6PIhoNadiE6VG7Cy2RrPT6mbD2ZxR9deemQGs5weMEoGInLGRNqmRgM/WxnuY2tHEmfbaaktl7dbSjALt2TzCWg/VSMCLNd3WZ2tl9cg19bpN5/R//5Dfq2bCFG4qzYj4vcjm1QOpqax53LuHkhhKZKVxrzybB9ReIlB4fiCvPVuFb5DTn71hLaukcOgZmdFUFomM6lw6ddjFmq8q+y61pbQ7+yBrT2byhna/jW8gjX3F434otyyrpUSgdP1ITne81K8b0ZeQlsKQXz+SzOrtYJyH0uuQBjA57FrUS4vmqX0M1ckhP4isO6gRyfmqzJhX10Ugpzk9USmVZW23JrpSJLM55BWOdE5tLefXdt9W7QMVpDBU7fV5EJlr1WSH3TDyqazhaMrRGmPc1XYwTWFnjU9q6d6QkCJHtilHSx/ZpOkhanxdHLTqryLSK39epdrFwRirgyhKM+QuLGrkyKO+Pqj24RbZwtFkTnfYD4Z2uR7Zul5F2i5sZ8xtIh4jySxGUzlk8koF2qt3HE2bOb9ZiyjNMIID5uhLKVvjVLveRaCqCLsROQIK57zowhLWNtiGg+/R14ndenUaHABqrM+UoqVhv8c2OCAfEktm5cyMt0B7X0w9he80OFBLZiZuyip5CzbYYr0K7QlpQy46AJi0ayVXTsdelAjYXVlfXnter1/XN9i5fEFgQ+gWh/YA87gnMnlk84p+cPNgbPTiNmWb5vMDXnMwzyarJI99NeV3QLXnrIz1aq3B1wMbfmODnTBpL1yvIjhQ6SG8SrVPTHlDrSUCtrUvXsvD1ZhMIoQvGE1lMZzMIq9wx9EXsaiqc3qNyJE1giGiL4wxPYIh1+1YTzHKjqNT7UD1BjEhaQG0KIBUrB4NGI5NQnIAxOtl/eaHaGXaa4tgaMY8UCyC4UNCmy8JrbWc+j1j3sjRl/YGZ6fwhfZaSjMMh92n18WatEsRDLmmVx73sXQOisL1w4+VlghUe6BKHndANXCGdq8pgiHXFFrX60gyKznsB0G7pdm90C7ezxot1Tfk/sL1OprMGodOK45S17ZerYdmRWmGHH2xO8gmMIIDldmaarMbcj2y0CSvV6FP/XpOspM+vQ+3rB3QnF6Hh5Vr0Q6Iml678gZztDQpOY4RyXEUjMrBgQoc9lp7U9uVN8ilGWLcxetF6Y/YcADS8ymegd/rPDhQS4mA6IEvtIuvWTOR4utJ7dpf8T0Z1XE02oFWor2a9ZoUGTG/x7ReRdlXVLPx4rUmxzFgtTW5ijqtyNprOT9gtSmAUcImZ7blDbbduFcaHBCHtg9aeQNj7HbG2KuMsW87/Zn6pxyN3WhDyBx9MRWrF0yObMWpXo+HIRrwVvcgkhx2oclU3qA7B76C3Vyh9hyyeQVDiWxF0dJqDWJC2ukD1g4IOf30Z9jisMsRR127yXGszJjXcjWoKG+xi5aKeSO+nsyYI7269iod9oaAr+oSAbUe2RhfQE0BF4tgyHV2snbOVYenP5bWjGv5U/hAbQ+iRFqqA/fLDyIt5Rgq1B620Q6o82ag4tKM2s8PmFOOOVPXDGODbY2W2jxEq3TYq4uwG+tVXDwiZ2Yagj5TSy25NCNiExwYSmSgcOeRI/HZtUS9TOvVEhwAjGyTns3TDntGbdbrQNz5YWVVe3XnBzI5Bdk817XL5Q2iC0tQqjlVtIyYvl5tgwOVOey19qYW4xcKlCjN0DbepoyYNG/GUupGqX9MddgrCQ4A1a3XuMXGA+YNdqN1vWbyUgmbzSY1Xl0pVbVZpWhAZDCM9SrWgnWDncqqly15PEy3rwLZYT8YZ5Xk9Wp3QN8aiBRdZMIBr/7vJZB9Mqfa1TVf+XqtyulljF0BwMs5PxvAVMbYPCc/V+vkACwF35b6EXngZefLLvpSaboUqL4ljNwCSfzfFC0tEsEIBdQeiPKd5aPJrH4JQaXRl7qkHGWDKKXERARDLisRnytrByo7GGNor9wYKgrXWhpJGi0tkCJ+rx5hB1Sn0l57Tku/VOiw19ASJp7JSQ54oTEviGBI5Q0F2Y1kVq8rdfogqmm9ZuwjvaaDG5IzLMob5M8VjMgPIqcHNGoc94DPA7/X2CCIfrZGaYbxOwljHrTpLzmaylXUXhAA/HUoEZB7rsqbVFMK21JnV2rcndYIAmKDXYXzItZk0Jg3cgcEa0utlGWDHbU4jtm8guFEtjI7GfLXls2TotTWcRddWJKZvN6hR8wjc1bJOHNSaaS32hKBRFpyYv1qeVFe4QUbbNFSKynV9MrzRuHqc2FAu0nOsfYaWoIm0ja2RtpgW4MDssNudb5GtMyMnIIvR61ZJaMkxrDl9oEN1TeQy0pkqnHYG2scd8ByVkme84HiPpldpLfSw4+qfv9BK284H8B92p+fB3CO/E3G2PWMsWWMsWV9fX3610UXgeqipTk9DRDyGQOZ1aJoDQEjgiEbxFDAeHB1NgbRFPJVPcDRoM/2etTy2s0p/7AlCtAgRcSSWXOkFzB20nMnNWA0la24NlPXXsPENg6D+UzR0gb5ASWfwrc4a3MnNWBUuzhkLO28V2wt2uUyEVW7edxFaYbQnssryOSVgij13EkNyGhN2sUlA5VoB6o3KtYIRiKTkw6yGS21xNgb0Refrh3QogBx5/VSZu3VrdeIZQ4kM3lTqtecmcnbzhlANeZ9Y2m9Gb4TjC4C1T5EreNuLs0IWxz2sF+NNoq1OqdTbUEoxh2ocINd9Xo1HpaA2KSqX4tZ16ucLtWiNYwBfi/DjLaIOSNWofNVm+NYGOmN2TjsiZJ2Mqf3Ba8sI1bdYbC4rY0X4543xr2YjQ8Y69Xc8aOyOaNqqW6zZMwZw6aY1qslzW6nHTBKeiqbM7XVxVrXqzk4YD5MK9f0Wu3kaCpX8XmZ2oMDxmZO1Z6zdXpTWXNgwzruwmEHnHdGqrZEQNVubPQCXrW8KJkxl2Z4tAyHOu6FpRlt0QDaogFLNm98zypV6/RGAYjO66MAJsvf5JzfyjlfzDlf3Nlp3LktUlDV9elVi9UZY/B4GELaQYG41cj7jYijV2vsL743b1IDmiN+bWILY17hg6hK7SaNNlEA8XVrTS+gRsUmNwUxvTWspUsrS/Xq2mt4EEWlhWndzQGGM5y0GH/xu506o7WqiJ2q3YtMrvISAaOsxNCezmkney3jzrnRUs2qffHMVgDQx77SqBdQSxTAHMEwz3mvHh0Qabti2ke11FclDnttfbXNp8HF18x1dqKmV5034tBDg432gQoOnarvr753tR0QoqWi1DZZJWst9YKuRjSGfPq4A84fROIzarmcwnwYTNFLM8S4qHXs0nr1+3T7PKejAW3RgKU0o7Kxr6XzhF1Wyba8wbLBbtBKOo6f2lR1Ni8aqLYeWZTf2UWp5XEvrh1Q53wmp2AkkUWsiuAAUPmczyscKanOVT5gGk/n4NVLM6T1ms3rrxMOq9lOVrhea9ik2tX0yramsNuKYjvuhvbKsnm1BDaSko03ggOKVFZiXDKjl4FZtJ86Q7OTWkCsMeQ8OCBKBKqx8WqZiOo0M8b0Ona5NEP8XuYuNx7TBrU57MeIdFi50kPuByvSGwMQ1v7cUMn7OPHMe0aS+Pmzm03XBicyOVPdk4jayf1WAeg1U2Inypi6YEN+D+Z3NaIp5NcjvZW0gwGcnexNZvL4wRMbTDdQ2UUw9F63BQc0Cutim8N+zO9qQlPIrzkAldW+AM7GnXOOnz+7GT0jSUm7JeXo9xg9S1Pm8ga5vjEkaZ/eGsaUlhDimTwOjKaq0O5sJ/3Hpbv0FiiqdnPKUY4CmMZd+7qIDIm2X81hP7wehlM0o7JvJIl0Tqm4vtGJ9ifW9JhuH+Ocw9RjWDJ8ovWctdRHrukVfZ9Pn90GQKuLrfBAktNTyW/sGMT9y/eavpZI50017IDqsMulGcbDNWdqt9ZUoD1X8cFNp10EtvfF8Jt/bDNrlyJHclcVWbvYeCe1CIZcEuNhwPzJ5vXaGvHD53Vubp3UZ44ksvjRkxv1WxoBddyFkwKITWrOVJoBGOcKjFIq9fWqrWlEU9hvKs2o/NBsae25vIL/e3KjXqoFyBtsQ6NxI5u8SfXZRkubw37Mm9yAlkhAL+epRruTEoFbX9yGrb1j+t+N8rvC4IBZu7rxFq+XtUcDXiyc2gQA2NYf07RXvtErN/Z/e2uvfskRYGTErOtVOL3RgFfvmiHeP5NTTNoB4LRZ6noVjqPTg2CqdmeO4z829+Gx1T2mr8k1vcKGWMvACsobitlJbd44vUkOcB7YWNs9gj+8ttOsXSrbkc8PCCe0oBVrplD7wqlNaAj6jKBMBeMu9JfL5h0YTeGnz5h9MrkOXOi3BjYA4ZMZ484Yg9+rtqZc0NWIJhEciGXU/v0V+GTVBPOqdXqXwyhpOBHATqc/6KRE4Ol1B/DzZ7dgv+YgAerkkA/giDSR3HoKMO8qxCRijOHO607HF86fi+aw8SBqiwbhcdgORtdeZoCX7xrCb/+xHW9pV78K7ao2cymAKM0o0C4d0ACA//vgInzvvcdpO6JsxT1LhfZydbE9Iyn8/Nkt+m1GQGFNr9wXVnTNMGm3OOz/dvF8/PqaU/UFuqMvXpV2oLxR+d/HNuD+5XsM7enCyBFgRO3kRQkYfWyF9o+fNRN//PTp6GoOmbRXVkvtLOJ48wtb9VvfACCTV5BTeJFaNdUps7YDk435uxZOxu8+vhhnzGkHoDb/rjZdWk77n5buwk+1W98E5uufjYMY1s4TZu2qOTpuahN+c+0peO+JUxH0eaToi3Pt4jPKaX9kVQ9++MRG0yZVTjkyxvTskaxd/F6JTM5cIxj04c7rTscn3zZLtTWpbEU9eg3t5aOlL27pw6+XbMOm/ZLzpXUfEXXbxbUb3VY8DPq5gZs/ejK+fukCw07GMvB6mL5+nWkvP+6bD8Rwy5JteHGLUf5mt17lvp/yJlWMu3gdAPzn5Qtx44dORHPYj7F0Tt9gV5oRA0qXCKRzefzv4xvx8CrD+ZKvkwXUcRddVaydJwCjj61Yr597+xzc9anT0aI98KuzNc7KkX7y9Gb8aeku/e+iJEbWDgjHMV8QHBDPH1EG8f6Tp+HO607DgimNAICe4ZQaHBiHEoHbX96Bm7Vb3wz9+ULtVltjaWcqXnfmnHb85tpTcMnxXQCkSG8FpRmic0g57Q+8tRf/89gGs/ZMTt9MFAsOBH1G6YB84LerOYTbP7EYH158lLZecxWflxGfUU770+sP4Kbntui32QLmcQfU+WDNRKpf9xrjLr3+jk+ehi+9Yy6ahF8TT6M1EqgsOFBFi0FnldqF/B3AS4yxqQAuBXCm0x8M+71IZ0svSuE4yensfcNJtEiGV6SPbAc4kzcdQgHUyQ0ATSE/tvXF0DdW+eQQu/RqtDcGfXq/xbDfi76xtCn9or6/fQTj+GnNqvawD6OpHPpiaQS8HjQ6LLQX75XJq4cTivV9LKYdMHaVovk3IHap1giG2YCK65U3H1AfzNv1CIZzoyLGIZ0rPm/E7UyZvI32iN/0PnoEQ5ozgBHpFfOmvSGIsxuCWKndGiO0V2LMQ7ohKz9v0qZxVx/YYtz13b5mVOTaTECN5GbzXP8dQ34v3rlwMsa0jhl7hhLIKbwiB0DXXmLchXZ53FNZ9TKJgnHP5pFX1NdFg2ofZ8Bo+xWWNqmXHD8FgBr1Fc7XYi2SVIl+J+MOqHNeLXPh2DecxNSWsP4acWrdrpRKbFJlW3PeMZ2adp9en1mpwx7ye8tehKNrt8x5Me6A4Thand5wQH1/OSMGACdrWQ0j+pJGWzRQUXAgJEVoy2q32BrGoN9AJQ6eWkszxO9kremdO0l1ul7ZqkYxdw5UvsEWgYZUVoF2q30BKa0zUMZmvbaEA7p28XvG0zl0adexCgfHamumNIcxpTmMJVq2x7A1ldvJcmOfyuZN2oUj0xIxxh3QIo7prH7ILGKxk+LzGkN+nD9/EvYMJszaK3AcwwFndjKVySMj2aPhRAaxTK5w3IuVZmS0ml7t716Pams45wh41Q12Jf37AWNjXFa7Nu6cczDGoCgc+0ZS+jMy4PPA52GmaGljyKeXDoigknxw8MJjJ+uvEw770Z0NjrUDWrllGRsvDuta502LZGsifjUIIN/UChgb7LDfsPEA9IBMU9iP7uEk+secX0xh0l5m3K1UFenlnI9CPcy2FMAFnPOR0j9hIB9OKIZw+oQTsGcwgWW7hvDOhUbpsIiWil2tdYDl3ZyMHn2pMNWraveYIkK22rNCu+gGkMfja3twka12S/TFb5QI+DxMdwpk7XmFY/dAAh0V9IpVtZc3iNZxB4C/r9iHRdObMVkz2pGA6jznRASjjEGUtQPA9ioivdYLAuwQmtPSAvj7ym60RvxYPFN1lsz9YvNoCJqNvFPt1TjsZR9Embxl3LvBGHDhsZPM76M5MA2WKLWuPWDWLtLthnbn4y5S+6kycz6VzZvG/en1B5DM5vFOzSDL9cgxPQ1sE8EI2K/XwXgGg4nKo6Vy7Xwp7YCxXtftG8XW3pjJ1oT8Xn3cAdiWI9nV0MnRl0qcF8Cc2i+rXRv7kUQWL2zsw0XHSrZGe5/ClKO37LhXmy518iAyxl19naJwPLRyH86Z26HrEeMuSjPk9WpXBiZrB9Q5H/BVHhyQ9dlhtfEA8NDKbkxvDWNBV6OuHVDXjtzasVgplZ12oLKzD3JqvxTWDfZDK/ch4PPg3HmdJu2qw24ObABGlNo658VmS7c1FZx9kD+zEu2PrNoHzoGLFprtpNhsiB745stklALtjDE0hf3YM6gGB6qZ8079GrFJfW37APrG0ma/pkgG2xQtLenXVOawA+Yb+Ipqt6zX7uEk3tg5aLI1oYAXyaxRuiOXy4iskujQU6A9WZ1PFnLgT1qpuk8v53yIc34f53x/JT/nZICFwRG7igfe2gvGgA+cMl1/TUQ7OFUQfREHNKQaQRkRfakmXRryO98RicnxzPoDGEvl8MFTJe16lLrwgJu1WN2kPWQYlUofoiEHxtz6IFq3bwTre0ZN2sWCG0vl9K4Zqnb1/0bqy6y/STLmcuP8SrSXmty6w543HICn1x/A+06ahoDPuC5TvNbUNUMYc0271SA2aQ+sapxeJ+MOaNFSyQF44K29OGduB6Y0h83aC0ozrClHe2NejXbGGEI+Z8Y8LUUb71++F9Nawnp2xe9l8HqY1nnC6JohRzDUK1kL50RTyIddAwlwXpnDDkCvuS2nHTDm/P3L9yLg9eC9i6bqrxERR7lrhvi6fjDG5kEkzg/0VVjfqGp3EC21PEQfXr0PmbxSaGvsNtjahSypTBFbE/Yjp3DsGUxWPu4+I6tUVrs27kt3DKB7OFmgPZE1d80QX88pXG+BWGBrpPXaEa0sOCAeyiVtjeX5tG84iZe39uPKU6brEXFri8GC8oaY/Qa7qYYNtuhqVCqTqmfERJAgl8ffV3bjXQsn6w633KbPboMttFtteEPAB8aqdNi1ca/ETgLqej12ShOOm6pmQ2Xn1to1A9CeW3nj0J5MU9hXVVAGAII+b9nggHXe3L98LxpDvoJgXsp2vRqOY7H1OhjPYKiK4IDq11SWwX7wrb3gHLjS5JOZgwN2G2y7576wk5UeflS1e8qOu5WDeiMb4CzlmJAeRMIBOPvodkyTUo4hi0E0dhUe9YBGxqgRlGkO+5HKKjgwWk2kt7zDLupd5Yk9tTmEszQHADAc/1iR0gy5NtOqHQB2DMQrL81w4DgmLA+iB5Z3I+D14HLJARALTtS/Wi9PKBctVbVXuosubxATlkX56Jp9yOQU06K0dhEoqr2Iw75DS5dWcgrfybiL74u03es7BrF3KGm72UhkRPTFiIaZtBeZN0L7eETtEhkjbbd/JIWXt/ThylOm6Q6AuG0wmVFM4y70J7Oi/6T9eq1auwPHUZ83Wn39w6v24Z0LJ5tLBAoOaBhjr3YsyRUd98F4BmOpXOVpOycZMZuH6IKuRhynHYay1+4za3dka8ZxveYlByDow8XHdZm05xWO4USmQDugznmvh8HvNTu1Ju0VRBvFZ5bVbrHxD67oLnAATOtVOpAqAjFO7GQ04LV1cIpqdxDpTecUcG6M+wsbezGcyJptTcBiJwPF7KR5vXo8DE0hY712VjD2ouWVk42e0L75wBhW7R2xtZNGcED9u2hn6tROVrpJdVIiID9fx1JZPLG2B5efONUUZBGBL7k0Q+i1loFZte8erC44EHbgOMobbM457l++F2fOacNRbRGzdqndWoMpmFc6Sp3Nc3QPJ6uz8WXG3coEOL0eR7s5QJ0ca/eNYM9gElecPN30GrGrEAaxWa9H8uk9S+12FcKoZCostFe1Gy2vimsXO2gFI8ksXtrShw9IDoCqUX2g6drFDtsvIhg5W2Nn1l7Z5AjqO+niDow1bffYmn14x4JJaJUe2GLS7hsx15xaSwQKUl81jHvQ5zzSKx5Ej63uwbxJDTh+muEAGAeqchhOZiXt9nV2AnHSNJNT0BTy6ZFjJzipVVO0lkEi2vjYmn2IBrx410LJAZCiL0OJTNFxL2ZUxLhUPOd95aOlKcmBeWJtDxQOXHGKeb2GtPScrF3oH03mkFN4ee0VOo5OUl/yvFm6fQCD8QyuOGWa6TUidTmUUJ0s4QSIdSy3LCvQnhfjXv/NhhGlzmPvUAKr9gzjylOmmyKbInI0nMjqmnTtZR6igLZeqxh3oPR61TNiWTUi/MSa/XjPoikWB0Ad50JbY6xXuR5Z1x6pg/YSTkDK4rA/troHp81qxYx2swMAAL1jaeQVbrLxQrv6u1ij1NXbeMNhL2HjM2Yb/+jqHnQ2BnHO3I6C90lm8iY7aT37UKykR6zXSjojMcYcp9lFOc9jq3vgYcD7TjKCMj6veplTIpMvsDVhv7doWYlVezVj7ziDnVfwwqY+pLIKrrTaGu19hhLquOsHUrV1XKocqVrtTjLYSWm9rts3ip0DiQIbL4J2ovWnPm/8PqSyChJFsu+yrak8m6ceGM3lS9tKmYPu9DqJvsjOl+jrevQkc3G22FUMxDKmui0x8MUiGE3SIuiooNAeMBZ5qcNsssM+kshC4cCcDot2zbntGTG375Jrpsppr9R5cRLBsJaVDMYzepN9gTDS4tCCiKTI2v3ewnpk+Q72Sg44yO/trDQjr2s/urPB7ABoY9AzkkJeqtsqdqLarF8d+0ojR2KnXtIByBWO+9SWsPlkrBQ5GogbKSwRwdDr7EqUxVTaok+8XyWb1MG42gpwpuQAAIaTZe1kEAl4i9YIAtY5X02JgPPaUvFAtB4EEQ+igZh60MJIYfu0CIZSpJRKsjWVbvSclGZYxh1AwXoVESJrz1pROiBfyWrSHqpt3AFndbGZfF5/mNtpByRbY7Nex017KRufMZ8fELbGmXafrh0oXK8Bn0f/2WrKeVR9zkszBuMZzGqPmE7MC7sTT6sXfIib1ZzZSfX3aw77KwoOiPdz4nyJzcZgPIOWSKAgOigCa7KdVPX7SmsPVf98VT/TWYlAOqtgUFuPBfNG20irLRoNDabyhjLaxyODLa9Xw04WrtekZmt8UscX0c40VST7bvINqt3oVdDDf0LKG8pGjqToi6hPCloWkOrcKnq9nHBuxJWyRY25/CCq4JpEAPo/mCPHMa/oDljQb9Wu/iPvGVINokgDmSIYJXZEQOXpF0cPImnc8wpHNs/1KKv+PsLpHRLGXDOIUgTDblGG/V49DdlZ4bhX9BDVJn8qmy8Y94hVu8VhLxfBACrfKKkRDE/JOjtrbWY6qxRoFxGMWDpXULclRzAiJbS3RQNFO3cUI+SrzOlN5xQEfYXRN5Gut17uEQ5I2ktkZoDq5nwl2sVrC+eNz9DeYNbupBwJqM6YZ8pllTLmcQdQsF5FNLo/ljZdk2xcyJIpGqUWVBN9AZyv11LagdLrtbz2SudMBY6jtl5TuXzB8ylisfHWwEa5zAxQi8Pu3E6K9WrWbh8csJY3lFqvlc4Zob/UYWVRj5xXOPIKR9pm3IUu4XxZN9jFIuyy9qqCA5VklfKK7qTZrtdMXr3502TjfRizdOgxa5cdxyrOKlVo44tqz+bRP6ael5Lr241LfErb+PFYr1YOfqTXSdrO5DiKAbY4jn61uXq/pS+dGHi1LYnNrkLezVUZ6XWaZhe/p3VyiEm7dzCJBulqVTlVXe+dqJN6r6QDhz0iaQcKIxjFHHbGmK6/4khvBWk73XHMKQVzJlSg3RzBKFbTCxhjX+m4i8+t5GCM+hAt1BDye9A9lFTrthrNEYyS2jWDWOm4i/dzmmZXr2ou3GyI90loxlxOOcsPolLr1e9lpoiAI+1OSqkcOI4i7Wp12EW0NFGkplfWW7Xj6MSByRd32EOacyvq5eTgAFB8vZq1j+N6lTcbZdarmDfl7GQk4NU3d9WefSjVHrHAccwqCFp0iLlcaCcN7XYdegBj7CvODjjotmItA0tlCx1HcSDO6rCLC1lKOeyGnazc1oT8npLzXc6wiuerndMbDngxmspiOJE12Wt5g11qvVYVHHDgOIr1oAbz1D9bo+FyZqaYw17sIJugmgx2JRmxYutVaLdG2OV2puUzM/XfYFs5+JFerUZQvtnDimlXIRxHq1Hxy7sKeYB94FxtMl12V1HpIQcHaXa5NEN3HAui1Orfdw8mChYlUNyYqz37NO2V7oh8Dh5EUvpFH3ebCLvQDhiHusppB6qPAlRzotougmHVLsZQjE1pg+g3/UwllCvpsXbNSJcw5rr2Yo5jydKMahz20ml2ReEm3UW1+70Y1q5WlQ+4hP0+Z1GvaLCiU/iqdgdZJSltV2q9qtHSjGncwwEvRpNqCVO5zMx4OI4pJ+tVT7MnLcEBY5NaKrNRjXYn61We8/pmoyAjZqzXxiLBAbuyEsaYZGuqDGyUqumVHEfO7SOO4n0MW2PjsBc5pFatdtFtpVSqt8DW5AqzSh7tANUesdmwzBujLtb+4ClQeVYGMFrUFUP+NxHPV/vggBd7h8ybDVW711k2bxxsPGBu+5XO5fWuNlbtKSlaaqe9lK2pJjgQ8nscd1tJlwkOpHMKesdSJp9MzPmhhL1vMN4ZbCsH3+kNGHWxj63uMd0MIzAPcPHyBoWrV8NaI70AoPBiNYJybWn1B6qW7RwsuIVK1m6OHFkfREbqy7oode02E9vjYXp6svK6WONBtGcwgf/34JqC4m85Yuck5dga8euRinLjDgCN1abtfMbEjqVz+NpfV+mHAK3aDQes8EGkOwA2EYywX51PAZ/HdpevR0urjvSqqervPrzOdH2pql3VbKTt7B3HSMBXkOoFjLUgPqtAe5URdsBszH/1wla8srXfrF0yNiJDYPcgigS8BSUx4usltdcw7rL2vy7bg7+9tbfgNXqnmBKOo6jd7bNGev0+XXupqFfIb74oxwmy4/iPzX0FVyWL7wHO16s1+gKo69V+g12f8wMb94/ivx5ZXxDkSJjspLDxJbRbNkqGdvtHmGhbVov2gVga//bXVXq3BkO7+vd0Lo+cwqFw+zkjtDNWGBwoNu6qdrFeq9ykat1Uvvm31aYbtFTt1uBA+fXaaUqze0vP+XD1GTG5pvfHT23ECulWU8Do+CH02znsVu0dloCYrr3u2TyjpveuV3fiybWFnVzleWMXlBHaB+IZxDP5gvXqaNyrCA7Ic/7JtT0FVyWr2m3Wa5Hywb1DZp9MlHOqwQG7zEY9bI2Ct3YP4canCn0yKxMQ6TUG+N5le3DnqzsLXmNfP2LvwAwnsrbGXH6NjJjYclmBU+ST+I+t6cHNL2wtMOZm7WJy2EccVe2FDnsx7UD10dKgNO7/2NyHv7y+G3uGzAYxaTOxrc2kQ0XG3aS9TASj0ont8TAEtAzB6r3DuH/5XizbaTaItpFei3av9j7DiSy8Hma64U+/+rTMuFeXttN277E07nx1J57b0GurXegvFcEQp/ArGftqxx1Q567Q95sl2/Dwyn1ltCu2DcgdaS/5EK183INa2o5zjj8t3YW/vL674DVWx9HrYQXXYIr0n/V0seNxrzJKDajr9aEV3fitndPrIDjgaL3ajLvXw/TDwZW06JM/M5nJ47kNvbjjlR36v72uXUS98sZmwzpvzDa+OjtZfQmbgjd2DOKvy/di/b5Ri3bDxhTbbMja5atVA15jU13eTla/Sd05EMfdb+zBy9I1z6p2Y9yBElmlKtdrteMOGGVEubyCX72wrcBxNEd61XkTsrGTsnb5/Ih83qHe2uUWg3e8sgP3L99j+r7o0APINt5+3MUtjp3VjHuVQRlAtTX3LduL37+ys+A18iH3clng4UTWrL3MuIsNathfWf9+WXsym8cTmk9W6hwEMEE1vYDqOMbTRk83GbtoqdVBlSeB9VCP8Wf7h2/Q56mu0N5nHGSLp3NQeGEKz/QgKmLMi2mXf8dikSHhtFf6IJJLM8SYW8feXJpR2pgD5gXmTLs6oatJfYX9XqSl217iluiLPGdyeQU5hdsaRP2KYcvVqkJ/uehLZ9VRAKMvc7FxB4yxt3MczfPG+djXWpqR1hzHeCaHWJFxl7XbOezmeVNszts3Lle1Vxc5UnWptwfG7GyNJeUYso2wF1mvDh32SsuoALPjGEvn9Hlv1m5E64rbSak2V3IAwk7Wa9iPxlDlwQG5A4IYc+vYm0qpitkaSZfsiMhfL/aQrLakJyjZ+HLaM3njoHVhcMD4uzx3xZW1QAlbU8N6FSU9hnbzvJGdF7U0o/B2MsAYY/kUvvz1gNdTsDkEDBtfXSmVurmMazbFOu6prMXpzRU/PyAoPm/qayflmt64ja2x1iOnbW6FUzWWX6+lOvRUa+MB4yKV8nbS3tbIGosGIm3Wq09rCVrNnJF7gseK+AZWJqRlGWA0jy49wHmks3l4mLr4TO8jP4ga7XdExQxic9hf3S7a5DjaL0wnpxyLTQ5Zb6kIRmvEb2twSmr3y9rLGPMSuznTQ1TSLq6ULacdqD6CId/AV/QhmlP0w2y2BlHTZjUOYt4UcwDqEX0x5oz9Rgkwxr6U4yifwrdqtnP0azlRLSIYyWweCi902G0fRGUdx2LR0uI1gtUZc+NkbzydLzCGeYWbMgNqdqC0w95RLIJhM29Cfi8CPo+pDti5duGwq7rF5Rky5uhL8cMldtplvXYPUUB1Aqoad2EnpfVqHfuUqZTKgXbZAZC1l3Ec2yo8hS8Oa5mDA/aOYymHXXZurWMo9BeL9DbVsF51x7HYBlu2NfkSEUcRHGgwBwfE72S3KZe1V39otnxQBpA7xRS38UBhGZigVE1vtdFS0cPfbpOaLLCTDrRbSjMEpTr0VKXdSSDSJoMd8NpHeoHi67WUb1BtdkDoK7ZerVQWS64DcouJuHYtKefclP6TjXmqRAskgfVwif5ZRYxKV3MI01vDtt8rrV0a4Iw0wI3Ga3SDWMqYO3AAihnzruaQ7UbBsfaMsZMu5sCY0qUW4yb/LvKiFFfKxoqc0ASArqYQGoI+U1mBc/0ey7jbay/VNQMwG3MZMfalxp0xYGpLdfNmNJUtqj2ZNf7uJIIhn8JXtavLOOjzmB5QuvamEABgemuk4HvltXtMV2aXfRDZtFsDzGuxWLrUbuzbogEEvJ66rFd/3qwrZdFud5IdsESOKkyzdzXVaGsyimnsAz7j8+WbwcodBlO1V7bB7moKIlcmVWirXepNXW7eZHJ5aYPtLJtn3mzYO19dTSFMbQ5VHBwAjGhpMTtp7VYC2G+wRSch60a5XClVV1MIfi/DJG3dVqbdY9pgl84qFXe+In77syORMg67YWuqmPNaCZuY1yWDA3mjPWKBdt2WqxFE/etlNqmdjUF4WJXatfeOZ3KmTYeu3cbW2PUxjhRdr+U22B40hXzV2XgpuyFufVMUbnqWGHNeDX4EvIXPGpP2aGXrdXJzyHTjrmPtUjDPmDel/aMJcHpF6ktdmApXdxjiHzKbV5DNq4Y2raWPyqUwrO2b9NcUMSq/ufZU24VeDrloumyJgCkKUHn0pZhR+c5lCys6qSjwehgCXo827kWipQ7aN4lDX8lsvuCayXDAi1javn0TAHzqnNl4z6Ipto5ZOUT6yNBubxBND6ISO2lriUW56MvFx3XhsS+fW9XCDFuiL4UlAkYEz0kUwBoBKqd9flcjHv3yOabraSvSnis/7rL2JptNjXiINlpq6cNl1ms06MNjXznHdN2lY+0BcxTA6gBVEznqrHC9/vkzZ9iOR1ntRTIz8u2IdieqC6IvJltTmcP+oysXVawbsC+lKpg3Dro3hIrYSdGzOpNXimr/yoXz8ImzZlWnv8DWOMnm2ZfSqdot67VMecOVp07D4lmtprICx9oDzrQD0AJOhWdOAGOTai3NEc/XYtpPn92GR798Do6f1ly19pgThz2bLxqlNsbdGhwoPecnN4Xw2FfOxTzLRViOtGtzV3RYKPZsBSSHvcS4Ayho7VhKO2MMD33pHEyqopRKXq96CV4mpx9mtXbosTu4CRRfr058sl999JQafbLi5YNWJs7ptaSq7dqBOU5hVFDwDVQXrQMMo5yUFmZRx1E6oGHXbk3X3mi/IyqWZq+0llcmqEXtjMlR6kFUwnEUEYyofbS0mPZo0Ic5nZUbFECKvjgwiOL3K1neUKEx93oYFlbhNAod5nF3kraziVIXK83Qvm6X9hJU8xBStat9Xge1bhnltReLlqpfKxZhV/9sb47mTW60/XpZ7doYDms3I2ZyCrJ5Re84UmlZiXwK36q32LypxlkHzN0bipYIWA7G+GwO4cnOeKUOezWRRsAosSmVmbE7NGudN6LvLOf2G71MUrGtEQTUdGk1TiNgdFtJFIv0OihhExqB4qVUxTKRQZ8Xx1Q550M+9RBX0YyYNOfHUpqdtH2+ejTtxTbY9uPOGKva1hg2vth8tziORbJKRjbPGthQNRfr0AMAx06pzsYLv6Y/Zm8nC/2a4gfZABTU0ptqeovYmtkdUduvO9VuLREQTq/cO1m0Niv1bAVKlDcUmTfV+mTy2YdivoGVCavpjaVzusGQRdpFjkoZFOspfNNBtiJGpVbtaSmUXtyY54s3cS6SthMRDKD4xK6FsN+LdC5f3JiboqWV18Xq9V51Hnfx3mmHtWqj2unX0g+iyqKltVBu3GWDmMjkVKNSIs1e6UO0FsS/6UARY251HIs3jBcN9+21A/YP31rQr8bWrvwELLam4AChfVZJaJRP4ctflz+rXshpO7s0ey5v1K6XGveiJQIOggPVIrqtmLIbJRzHYuVIjDF9I1ds3tRbO2BklfTDYEUOb4ozJ6r24mNvzSqJzVKpTWq1iGvDi50fSNjaSfv2iICddjHu9XcdRD1ysQOEiQJbU6Tdmp7Ns99gj8ecsdqauFYiIEhkrLam9HotNmfk19QLMR6itAEwj33huBcrK1E1MmaupR9PW6NHenOKvkkqV95w8FuWiYdo3OizGkvn0B9LY8XuIeeRI+192iyn8MdzgM27CmOAU9k8Xt6i9i+1pu3sDuGJCAZQGPkKj7MxlyOOMa2e+vmNB6AoXCrNkBv1l3AcC6Kl46ndY6qzE7/Dq1v7kcjkTPOmdARDiwJYa9XKpBxr0249hKdqXbVnGL1jKbPDntIeRCUjGNY5UzpKXat2wDDmYty39o5hR3/cpkbQ/kFUdqPkt69Hrkm79u9vtTU9I0ms7R4pjPQWeRCJzYQ1s+HkgEbV2m3LG/IYTWWxdPuA6QICw2G3SZf6jeCAHPmUDzyOx0Yv5CusLc3lFbywsVe9TtZBuzVZW9HDYOPifHlMNYJi/Jds6kUmp+jaFW44BLZ17P5i63X8NtjqteGFwYFlOwcxnMiY1qtua4q0Rzzo2rUxHIqbN9gbekaxdyhRJCBWzZypv3YxhrKtSWTz2D2QwKb9Y/ZnH0rYyWLjbv1zPbCOO6CO/UAsjeW7hmzGvbRPVjI4UOexFzrk5+sh273BGn259cXt+NjtbxTsKoqlMCJFI0dSyrHOk8Pv9cDnYUjlzCUCD63sxrW3v449gwn94Ifcb9V6CE9EMAI+j94L09A/jrtRf6FBXL5rCJ+6cxmWbh+wtOKxb7cmaywsbxg/58vuZG9/LI2P3vY6Hnir27Exj0yAw67WxSoF5Q2f/P0buOWFbUUc9uIRjIMZ9RJlCf3aek1rLeG+8cAa/MdDay3GvHy7tcLyhvGdM4DV1uTxs2c243N/XG5zsUbpgzGlotR1j2Bo7z2SzOo2JZ7O4e7Xd+Oa2143/U56qrdE5Mjaok/U5o+HdqHfWme3ZFMfrrvzTazvGbUtESjVOqtYWcx4ZWbMtaV5bO+L4ZO/fxNPrdtfua05yOvVWpuZyyv4yO+W4s5Xd9rbmhLrtbCUahzXq14ioEVLtfH/8t0r8KMnN9m2drTttjIRc6ZIVul/HluPf7lvpc0Gu/xhZTvtgH2HnloIWcZdaL/t5R249rbXbcvv7A7hlcuiqn+ur8spbg8UZ8SAwuxGwc/UVYEDxANR1L4A6m65fyyNWDpn2m2o3RvKRY7MAywb/vFamPF0Xk/JJTI5/XfZo105KbQXuzEGUCdCZ0Nh03qhud4pDMCIlupp9kxOn+i9Y2n9QFW5WjWxSKwH2azXhNZVu89a75XXDw30jVqjpSVqeosszNA4G8S8wvWG6YlMDtm8gqFEFn1jactDtESUuojDrjsv4zTugHm9xtPqRRt9Y+nCAxrZ0m2/CqMv6u9ZaVNyR9r9Ntq19VqgvVT3hiJ14ONZSiWi1OZxV9drXuHoli6WKRWlFht1u9Zj4xu18xacxJdtTcpmg237IPV7C1r0ia+r2sdn3iQLNtiZAu1AmfVaZt6MVwlb0hKlHklmkc3z6rQXWa/jNe6AVBebUTOR/bE0ekdTJu3CsalI+3hu8uxsjbZereOezpcoAyujvViHnlqwt5OqT5bM5tE3ZjjDJVs7FnHYA16pnel4rddM8fMDVg7+QTaxI7KkHIe1+iL52sS01s7GLnIkBtha+yJ3FxgPYx70ewu0i0GWtQtjXmxXFg54bXtICs3jUZ9ZUKuWzuuO2FAioy9MhRspgmLRI7sb7cq1/apJe0A0LjcmttA+KGkHjFo1+9t6itSqiQjGeMwZS5o9ls7pGgfjGdMYj2mRo1JRr6L1yOM07oBlvWbU9RrM5s3GPFu+72ehA6COe7G+n7WgZ5UsabvhRAaZvGKKbAhjXs24M1b/emSf1wO/l9loL7STInJUbN2FA17bCzLG2wmwljcIG983ltY79Ajt/v/f3nvHSXKU9/+fmp6cN6cLe/l0SXfSnXI4ZYkkggCZZJIxGGNjbIz52firL8YYjMEGgzGCLxZgkogiCSRQzjpl6XTSZV3anCeH+v1RXd3VPd0zPbszOzOrer9eeulud26ntqa7+qlPfZ7nUYhlclHA6y7Jwudfr+/Yi8irY0xk81rb88mEySKQqny/2tli6iNsmOe9oM37VDJr2OjNalYq5wGMPu/1v18pZWvldCqHqWTOeuxlTjeqrY+8EPj6Zbxf2dxPJrJGT2/Ofq2pdDpQj2vGdp1Ur5uTJXGNdRMfu4BdLGdar/t1MpkDb45b00Q2QkiMEHIrIeR2QsjPCCFVlxLggYj5GIAvKqem0wAAj0LKHjl6FFZEvCdWmmFc7+Oj0rHnSsauBQC2veE96LHIjl6MBA1RwZgSgq9UrqAl0s2k7INeNvbSh2g9j4+YV830EOUPomQOqRx7cALlj+2iATc8CimpgrGYSQ7pXFFTqSdVnx0fe6V5B/RamCVjr6PSK17zc2n2IJpM5JDMFqC4CAhRkzdsytk0Yuz88y+5X1Ol92u5/IGQ1w0XKR07bykb8JRamGqB36MYx54tWI69nL8RYHPfu8j3q8+jYCaV15LtDOvkFBu7V3GV7eLHxu5Gr9UaX8eAnVdbSQgqNZ/3STVwLFlrbK75tqDHVhyol8JepGycgEkcSFSx1qj+7+6oWRyo5/Op9H4dnklr1WMsn08W49DWmph5ram/NcOwTmbymE4yexLfYOtxjfVaE9HGvnh+ZHPehjh2ADg5JcY19rYSxUUQ9lnfr/Udv6tk7OWoVul9K4AvUEpvJ4R8FcDVAH5RzQ/gO/rxOaNaOm3aVcQC3rIPIkIIvvOes7HaokxHwKtASRHt5q4lfrdiGnvBeuyF8g+iz113OkI+qx12fW/Mk6YMTT72kRl2bNoW9mJsLoPZdA6KRQkkAPjoVRs0L5tx7PXdbKRzxgcRHztXX2IBfeyA9WL+jnMHcd6aTtvSTnW5KbXAUb9uuFI3mcyiJ+svHbtFwH7l5h78zzt3lZR9q++8l4791HQKlLJd//hcFkGPgmyhKMx76ThO64vg6+/YiUs2dBm+Xm8vtXnsc5mCps6J9ytvG2417yGfG//7nrOxZZmxFJPoza8HLOi1Xie5vUFbJ20SYwDgv956RokVCaj33Lu0jR3Axu4zzXs04MHYHDtCtVsnb3jNZkMWPEcPHOujOGbyBYNyNCMGvZZrTekcfmD3Gly7vd9i7Px0o54BjG4RmE5xlToHv1dxNPbX7RjAqo7QolaKMY8dAI6r1/lkgm02+DVTbo0/Z3UHbnz7mdi5ss167Isw74BuLQGs4hrr+7U35sdN79qFc1Z3mMauXjN1mHdew9/R2CvENTe9axdWdpTGZHzua30iBpSukzW1N1BK/0v4axeAkWr+PcAeFH63C+MJY3LJtMneEA96KioYuwbbLb8e9Cp1U18CXsUg9ycsrBnxoAdD0+myCoZdzVdtJ12nIxiuAABGFeDkNL+w3eqikredd7vao3VVqd0K8kWqPXzEm3JCXRDjQbaYz5RJBmsPeXHWqtLrpq5lvzSLgH7Na0FvIqeO3aPNu93YfW4Fl2zsthh7PR+i/NiudOwAu278XgXIlVfYCSG4YlNPydcDi/EgSlifzBjXmvKK43lrOy2/HvAqWt3fWhPwKCVjnzbdr/GgB6ksq94Q8lkv56cvj1v//DrP/XhiTvt7IpuHO8XWY/NaM1dmrVljU9e73mNPZQuGBEKDWpotoCfqN641Ftd8T9RveZq3GN5Sft0UqX4qMJnMIg6PxVpTOvawz40L1pVe84uiOFqsNfkixehcxvB8shu7y0Vw5ebe0rHX9dlaOvbh2bR2DZ2YSqlKKDuxzJaJa3ZvKF3jFbUMYD3mHWDXb8k6qW6WxLWmnBAJADttYrKAR6lLhR6Azf3xST2fqlIb4rKrNSHka4SQu4T//lH9+rkA2iilD9n8u/cRQvYQQvaMjo6WfD/gVQwqAPNMGR9EsYCnooJhR8DrrsuFDbDga8LkfZm2GHtGrdNb7c6m3hmmJWNXL2w9AGDH/jPp3DzGXj9fLP+ZfPypXEHzIPEjR16SqZwKYIfmmapj4CjOPVfqsoUixhIZbewzCxl7Hf1eVmMH2HXDko2UeY5drVlah7HzJC5x7MMzxgcRIKw1ZRZzO4JepS5jB9h1Y1ZLp0z3K1tr7BNjyhFUbRv1UF8CHsU09oLFZkNYa6q87/RrvvZpKQGPgqR6jAsY531kNoN8kZasNeZOeOWo5/1abq2ZTDJvqXmtqcZPX8/71claE/Ixe1q5qhl2NGqNB4zrZLnmSeWo51rj5H7la818YjI29vqkkJWOfQGeXkrpn1JKdwv/fZIQ0g7gPwG8u8y/u5FSupNSurOrq6vk+z438x0BbDJGhAcR93sZHkTVXhwepW47Ir/XOHZxQRTHniuwurfVjr3etQSNY9cv7JPChQ2wBI1qVZR67qT5Q7FI9cXrlKiW5sSgt/pFJVDHgN1vMXbxtODUVNow70B1i3k9laNKYz+pLeauskk9dtRbweAeR49C4HaRknn3KARBr1Lx2M6Oem6wAx7j/Wrli2XrJG/JWq04UL8TMX+ZsVutNfOZd6B+HkHqYN4BttZ4leoUrLrakcrcr7kC85YuZK2pd84JUH6t8XsUeBVxrak+YG/UGu9XrVDlTvPKEfQodTnZAErv14lERtv0nbQSB6oO2N11XONdJWtNOapNZPMCuBnAxymlR+c5RkPWc2fYZzgu5ZmxC1EwQj53/dQXYSzdEZ/qmWI3oDh2AOqxXXXjCPvc8CquuhyZijd7d8RnsAjwEmxxYTGvdt55WaFQndQXDu8vzq+bbIH1Azcv5tWoL2FfPdUX+7EDWHDAzuc9aHO8vRAqjT2dK8LvNS/m1V839Rg7oI8/5HMj5HOXzDt/iM6l86DUOjGmHGFf/dQXn2nuJxJZ7UEkrjXzDdjD3vrPO+BwrZnHvAP1DWAAZlEoUnZCAJSu8fMJ2Bt9v5asNVWMn1to6qWwc+zGHlhA4Oj3sMTTep4qAXopT/NaE/C64BXEgfnENfV4tgLGue+K+ErmHTCfvlc79jqq1Ka4ptaJbO8BcCaAvyeE/D2Ar1JKf1jtIPnuLOhhpa/EYwCA1Wv0e5SyHZ7K8ZeXrcNspjTRqhYYJjjqx/GJpHZRcMTjo2ovjredsxLbbTx4C0Us4dUd9ePIeNJwLAAAsaA+9niguuIcV2/tRYFSLGubXx/tcog7ej5283UjzrvbJgnPju3L2/DJazfjvDXW3s2FYFjMbcYe9CqmYzvnY28LefH5N56OizeUnqosFCfzHvQoyOQKml+82vv1X9+wDau65tc3vhJ8/PxhYR57wKPA53HNa94B4GNXb6yLUgqUXjfHhTrgHIM4UKX68icXrcJVW0p91rXAfN08f2pGU0854lrTFqpurXntjgF0RXyGLnO1wm8KAA6PJcquNdXO+wXrOvHJazdj20Cs8ourxO9grSm1Ujm/Xwc7gvj067biys21v24crTVek5WqirknhOBL1+/A6ctrP+8Au19nM3mEfW6EvIr1WuOe/1pzw2s21+V6B/S593tciPo9JWNXXAQhn1Ix98GOD126Ttv01hpzXHNqOlXm1dUnsn0VwFfnNTKBgKC+hH1u7BuaAcCUX0r1iyOZzduWQCrH1mX1uagB4wT3RP3Yc2QCgD52wHj0Ve3Yl7cHbRPFFoqY6cwTLIZn0rZjt0rCKEfU78EfnbWiNoM1ETCpLwAwVGbs1c674iJ4x7mDNRmrGbNyBJSOPaAqjvM9+nrDmctqM1gTvLB4kbJ6o4qLYEhVvbT71asgkZ2/0nu5RYJbrdDXGvb/AyMsuUocu3Heqxu7XeJGLeAPIreLoD3otV1rKGUNT6q9ZtZ2R7C2O1LTMXPM9+ujRyZAae3Wye6IH6/bUZ9rvtq1ps2i3no5fG6ljmtN6RpfbuxA9YHjW86uzxovJhGXXSfdLq0EWLXXzSu39dVmsBb41KA35GWnSiXrpFmlrvJ043ybZNpawJ9RYZ8bIZ+C506Wjt2ntrjOFqpXerfUYYPHMV83fI23oz5pxxUwTzD3YwzEmULILw5eWqtePpb5ICq9XWFfydgBluUIsE5zzTR2q6OvIjWOnS+IyWz1ST31xMnYm3XerY7tzGMPeM3XfHPMPSHEaBFQPe1Br6I97HnAzsderfJVT8z2hkprTbUPonoSqDB27kcG1Pu1CecdYNc8tVgnjWtN88y7YZPqYK1ppnk3H/UCpWOP+N0gBPo13yTrvCgo8eZBRQr0RPxa4xK/aZ1spuuGi0ohHzvBNt+vftM6adXgoVH4TUKk5djdLs3e00zPV4PS68De0NCgN+hTDGV2Vqk1d9kRhj60ZlpU+FiCXgVhf+nYARiOIJplQQHMiqNef9F+7E10YTsYO38QAc0276L6oo99RXtQaM+oGOa7meZeC768iuZHjAdY4X1AXxA5zTj2sLqYc/h1UzrvzXTdiPOuj1Ebu8e0TjbhvAMO15omWuPFE7FuR2tN88y78STSeuxBr1u7brxuV93sOdUiduUL+/W8nLaQV1tr+Aab01T3q9u4SQXY/PbHWOAY9CqGTXUzbrCDXrezmKyJ5p3fr163S/Mdl6OhQW/Ia/0g8jfxhW20ZpQ+iHyqH5nTTBe2UX3RrQutFjjajd34EG3OeW8P+bRAty3k1co2BUyBY70aHswHs1oKALGgV1d6va6mXRDFTSr39YoPIvO8N1UAYzHvgDFg9zZtwM7G4iJAR6jFNqkmCxunFYQNo9Krj31ZW1ALKANel/Z8baax8xr+AEtUDAkbbHGdFDdIzbVZ0uMabqeKBzxoC3m07zdrXMPv17CNEFmyTjbRvPP7NWxaJ+1oyMh5327DjkhxoY8/iLzN+yASVS9xggc7hAdRk17YVsfsgD52gHVd4TTTEYYxqcdaLQ37POCiRTPNu8/t0sYlLioxQS0VFxVR8WgG/Bb3ayzg1pKPzAtiM143xrF7bMfeTIs5f4gGTYu5ttaUBOzNM3ZR2LAaO2AMHJvpmvHbBI52Y2/GeQeMa3xb0LzWsNc107MVEK55QRCLBTxo1zbYxudrU103JosAoI5dXWtKT8Sa57qxmnfFRbC8jeUX+UvimuaZd33sxhMxOxqr9BqUIw86hAdRsypHVhc2AC37vGQn2lRjFzI0hUVbzJxvhcVcVF/agrpaKh7BNNPYmYJRet3EhQUxYBh78ywogPmYnY/dKzyI3E2sOIr2Bl19aVfVF38TH9vpCoZieBCtUBNd/eZ1sskDAEBfa3iFHk4zzjtg3GAvb9fVUlEcaK551+cx4vdom754UFdLxeummeYd0Nc+nu8DsLFramkTB476WiOo1EGPIfehWe1Ihnn3WokDLqM1o4nm3ecRr5mmVXrFxVw8BhB3RKJFoHkm2KAceUsfRKWeo+a5sAM2F4eolkYD+tebcd4BVkWAjzceNHlLleYMHLWjL2HuxQVRVAGaaUEBzGqp+CBq/sXcyqtmfhA17akST4zxGlXq9rCgejVpACBWzQgJ6stqgx+5ST3spjrynPaQvtYY1skmmndebQXgc2+xSRWD3iZa4wHTOunVBTGjOKBfK9XUYq83/ARbPJmJBbz62Es2qU00dm/p/SqKAwGPAl+Tn2CbbWB2NGTkPtsHkeB9adIHEb9QRXuDePxScoTRRBe23zDvxiAyFvDA7zGrL80z7+K47AJH0ePYTPMO6Jm6YgATD3hLKiAAzbWgAPYnM/pxqauJr/lSr1rMZt6B5pp7o1oqiAO2AXuzjp3NOyEsG9xFmv00T79XRZU6FtBPlUJe1g4XaK6xm6ut8OsmFjR5S5v2VEl/voqnSnGrgL2JkvAA62teVNibeZPKTzcMtpKSZ2uznioJxQWaNeg11+kFLKT0Jr047MYeDXjYYt4K2eCmI8eIn819MwcAYraxR3HZXDfNe2znF3bS/EEUFccuZPY204IC2HvVxLGL100zqS9+b+Wxi/PdLKXiAHHe9YA9Kvobm1lht1CpIz433IoLbUGvxUO0eeZdVKkVF9H+bhY3fM3qi7XzsdsEjs2E3ditRKVmHXvYpxgsApqVqgXu17DNNVM69uaZe8MJtoOOdfXpaVcBcTenXxz68UvQ627axBhjgoa+GCougnjQi6C3eZN6xHkPeBS4CLtQFLX4fTpbaNqg1+Ui8LldWhkbw/GRlae3ieYdEMrZePUbMx40Hh81r9JberohHpeKC6JXccHVTEl4wrzzccXF49KSY7vmuW6sksHiQQ8ifnbPBkx+5GYK2H3u0oCdK15tIS88iqtpbWDivANsreGtwttCHvjcrJ2t1+0CMs0174BwoucxeUtDpapds449ZPLF8vGKG+ymW+MtTlLFk5mgV0GuUBRe3zxzL5aRNZSlDOljb964plSlLkdDgl6r3Vw8yNRSt9rurlmPAQIWyhEvvdMR8iIk1EAEmmzswrwTQhDyurUHUUfYi5l0Di4XgVdxsa4rTXRhA2zu+fUi7kY7wl641aC4aVUAm+uGl3MK+9xNG7BbnW7Eg2zeAVbsvmmVI2HeeYwlJhCGfe4WUByNyY8uF0F7yMvGrjSnHcnozdR94ABbJylF0yb88rHwNSbsU5DKsmdSR9infRbNmj/g9zBxwOUiBosATxQPCaJS843d2tLDr6ewz61dN810zQDmpFl9neS+8JDPjaTQOKGZ5t7YMEzfpEb9bngVF0LmdbKJ5t6YQFh5Thuk9FpcHKpa+vU/3onTeqM4NKq3kmuqi8MtTrA+dgD4zBu2IuL3NK0fWZx3gN2E/EH0N1du0Hpje92uebUarDd+t74LZUdI7EH0x+cNYtdgOwghTbyYM2XL63YZ1NJXbO2DWyFY2RFs2oDdsCB69QfR9uVxfP6Np+OCtV3Ye3IGQHMFjYDupQ76FLgFpTcW8OBrbz8Tuwbb8dChce31zXTdWJWK45vUL16/Hf2xADJCIfZmmnsxeHErLvg9Lq0yzCdetQmUomlPlZgv1niqlCuwFlUfuHgNXrmVtbLV7tcmmneAzb1ZHIgHPXjjmcsxEA+gLeRt4lMl6/yBDT0RfP6Np2PH8jhufeYUgGYcu+4tFeuZL28P4j//aAcu2diNXzx5EgDzt3NPeDNgd4JNCMGN7zgT63siODaR1F7fTHNvtU6Wo6FBL7s4dKM9AFyyoRsAcGJKmOAmWlS49yXoYx1jCNHLfJ25sh0AMJXMaq9vrotDn3eAHSHxsa/riWiv48d2Tac4ehV97F63NvaeqF8rY9a0iqNHQdBntmYwBePa7QMAmnjsXvF+1b2lhBC84cxlANC0mw1RIeLlpni5vqs29wJA85/MeBWEvfq8A8B5azoBAEfGEtrrm3XsAJt/fr9uGYhpr3MR1mq2mY5LATZ+URzgbVmXtwexXK3U07T3q0cR5l3RysP5PQquUQN2zY/cdPOuPl+F+Y8FPHArrpK1phmvGcAo5vFr/tWn9wMwXjPNlIQn+tjNY9+txmQjsxnt9c103YgnYj63SxM37GiMvUFYCJe3B/Hmnctx8fouw2uMx3bNs6iIO1FCCD5w8RrtouA063Ep96HxwOWPzxvU/EYizawC8LG//oxlOGtVe8lrmlp9UQOXqzb3oFAslni6mjVwFK/589d24rozl2FdT9jwGt1n13zzDrBN0qrOEF5/xgDOXdNheE2zH9uFfG5EA26887xBXLmpx/CaZj1VEh9EAPCeC1ZjQ2+45HVetwvpXPOdKgWEteb6XcuRzpW2Nm3W+1W0gb1qW7+hwQanWU+VAh4Ffo8LbsWF3Ru6cWgsoTWt4jTt2IWTgTNWtOF1OwawY0Xc8JqmvWaE+3UgHsAfnbUcl2w0xTVNejKjd8JTQAjBeWs7cbDM6xsS9J412I4PXboWZ6xsg0dx4bPXbSt5TbMu5gPxAD561QZctZk9fP726o0lr2nWBA0AuOHVm7Ub8R3nDlq+plk9Ux++fJ22C716S6/la5rVZ/fO8wZxxaYUAGDHijbsWNFW8ppmDRxfu70fbUEP/B4F/fEA/u2Np5e8Rqs80WTzvnt9N/7ysnXY0BuB4iL4wpu2l7yGz7u3ydSXjb0R/MVl63Dxhi4QQnDDazaXvKZZA/aAV8EnXrUJl6kPzg/sXmP5Op9bYUFvEylHAPCxazZimdqN6vVnLLN8TbMGX3960Roks8w7ev7aTpy/trPkNc069jftWo7T+qIAgLXdYXz6dVtLXtOsVTOu2tyL2XQefTE/CCH49zdvL3lNs877zsE2fOjStdg12A634sK/vL5STNY84++N+vHRqzbg6i3sFOPb7z4L33mP/esbpvT+9ZUbyr5GnFRvE00wIQQfvGRt2de4FZbdWyjSpro4AOAtZ6+o+JpmDRz5cXQ59AWxueZ952A7dlZ4TbNuNlZ3hbG6q1SlE2nW04FY0IO/umJ92dfoAXtzjd2tuPCRSmNv0lMlAHjPBasqvqZZgwBuOSpHszZ4uGBdaZBrplm7P27uj2Fzf6zsa5r1NK8n6q8YGzTrNeP3VBeTNdN14yQmE2mumRfgF7ZHIZoXr5Vo1sDRCc26qDihWR+iTuCWnpa+Zlpy3lv/XgVadPxNullygrdJFUcnyDW+MTSrvcEJfL6bLQmvWpr2qmnliwNo7UWlWRM0nKDPe+tdN628mDdruTUntPK8N6vPzin66UYLXjctHbC37tibVaV2wpJ4tjaZDaxamnbm+UXRTAWcq0EbfwvemK284dDnvfWuG/2ab715XwoP0VZca4xl+lpv/M3qY3cCH3Mr3q98bW/Nsbfu9d7a8966YxdpiKfXCa0ceAGtrfR6tYu7FccuFcdG0KxlhJzQysoRAPgUFwjQkupLK2/0fC2s9LZy4Mg3Sq14zSyFNb4Vxy7SvEFvCy8ogH6BiMePrcJS8Di24nXTyhulln6ItvC8A7zqRKNHMT+WxP3aimOXa3xDaOW4RnGx/KpWvGZE5jXzhJAeQsgTtR6M6T20DlatiFftLe9qwSS8Zq0i4ISlob603qLSrFUznNDKD1GAjb8VTzaAJXLdtODct/I1rzfWaL2xt/wJtuJqyWtGZL5K778BCFR81QLxtfJi7lFa9uLwtbTPrnUzqpeEWtqC897KqhfArheFtwxrMVr5umnl+7VZS2c5YUlcMy047wAbd6uOnVN10EsIuRRAAsBQ7YdjxOtu3V2FT2ndi6OVF5VWToxpZfWlleed19VuxXkH2HXTskGv4mrZEkgtfb+28hq/JOa99cYOcKW39a4ZkbJBLyHkawDEisV3ALgUwGsB/LzMv3sfgPcBwIoVlZsh2NHKQS8be2teHK18Y7b02Hmd3hY83WjleQfUxbwF5x1gc18s7ZLbEvA1vhWT8OT92hha2RfbypsNoLVjMk7Z0VNK/5RSupv/p375K5TSqQr/7kZK6U5K6c6urq55D87XwoGjr4UvjiVxbNeC101Le6lbeN4B9diuBecdYHPeigo70OJrfEvfr63rpdbmvRU3Gy0csAOtHddwqrU3XA7gUkLIBwFsJ4R8g1L63jqMCwBw1qp2DHaG6vXj68oZK9vQFfE1ehjzYtuyOM5b09GS6stpfVGs7wmjN+Zv9FCqZrAjhNWdIWzoiTR6KFUTDXhw+rIYtgxEGz2UeXHu6g5sXx5v9DDmxc7BNtDWdDdg+4o4ZtP5Rg9jXmzpj2HbshhiAU+jh1I163vCWN0Zwqqu1nu+9kb92NATwaa+1ltrCCE4f20HtrXoWnPWqg4MxFvv2SpC6DxXS0LIXYL6a8vOnTvpnj175vUeEolEIpFIJBKJUwghj1FKd1p9b946tZOAVyKRSCQSiUQiaQZa25whkUgkEolEIpE4QAa9EolEIpFIJJIljwx6JRKJRCKRSCRLnnknsjl+A0JmAbxQ1zepPzEA040exAJp5d+hE8BYowexQFp5/lt57IC8fhpBq43Xila+bpbC/Lfy79DK1w6nled/A6XUsgzSfNsQV8MLdll0rQIh5EZK6fsaPY6F0Mq/AyFkj7yGGkcrjx2Q108jaLXxWtHK180Smf+W/R1a+drhtPr8231P2huc8ctGD6AGLIXfoZVp5flv5bEvFVrtM2i18S41lsL8L4XfoZVZkvO/GPaGlt/xSBqLvIYkC0FeP5L5IK8byXyR105jKTf/i6H03rgI7yFZ2shrSLIQ5PUjmQ/yupHMF3ntNBbb+a+70iuRSCQSiUQikTQa6emVSCQSiUQikSx5ZNArkUgkEolEIlny1DzoJYTcQAh5W5nv31Xr95S0PoSQMCHkZ4SQ+wkh3yKEWJbTI4RsJ4RsX+ThSVqISmuQRMIhhLQTQuYIIf5Gj0XSusi4p3WQSq+kWfgQgP2U0vMB+AC8yeZ129X/JBKJZKFcAbbeXNTogUgkkvpTr+YUNxBCjlNK7yKEvBMAKKU31em9JEuDswF8Q/3zfQB2EUJeA2AZgCmwIPgTAF4HAISQt1NKL2vAOCUtAiHkNwD8AI5SSt9FCLkBgAfABWDdhq6mlA41cIgLghDyRgARAPcAmKGUjli8ZheAzXz9JYRcC6CPUvrfiznWJuZqAF8BcDUh5DywdSgIYBTA9ZTSvKrS3QLgXZTSbQ0bqaTZkXFPCyCVXkmzEAGQUP+cBPBhAE9RSi8A8BMAWyilHwfwGQCfkQGvpAKrwIKZawAMEkJ61K+vpZReDOB7AC6t9oeqx5hzhJARQsgJQshfz3eAhJAvEkLeXOb7Rwghg4SQywghBwgh+9T/DhBCzgEL3NcBuBLAdwghRPi3XvXvJwC8lxCiqN/6GwCH+WvmO/YlxLkAPgWAryf3qtfHMIBr1a/1AaAy4JVIWp+aKL2EkOsBDFFK71K/VBC+HQCQqsX7SJY0MwDC6p9DAG4C8Ij695saMB5JC2GxBuUBvBfAuwC0g61DAPBt9f8jAOYb9H2ZUvp3hJBBAI8QQn5PKX2q2h9CKf1Lhy+9C8AmAE8C2AkgB7bGDgBwUUr/ixCSArACwFH13/wHmA2oqP59hhCyF0AGwCcIIf8INkcXVzvupQIhZBuATgA/BjAIYDmAm9VvP61+DQCmAXxpkYcnaXJk3NOa1ErpDQI4X/3zKrAHS0T9+9U1eg/J0uZhALvVP18I4AiAXerf/z+wAAZgC0kQAERlS/Kyx7wGXQoWzPwR9BMEmP68ICilRwA8BGBDrX6mzfsUALQBmKWUJimlObDfbzeA1xFCHgbwzwDeKvyzDwK4mFJ6gXpaMgfgfOHvl2AeSvcS4yoAn6aU7gYLaq8CcJb6vR0ADqh/TlJKi6X/XPIyR8Y9LUitgt4fAjifEHK3+vdbAHyUEPLfAMZr9B6Spc2XAawmhDwAFth+HsAZqp/uDADfUV93O4DXE0LuBwuOJRKgdA36JwAfB3CH+veBWr8hIWQFmPL6AiHkXYSQFwkhxwghfyK85v8SQk4SQk4RQv7M9O9v4t4/9e8uQshX1dd+F8x/zHkzgJWqteEJMEuDAuA4gOsopf2U0k8LG8F2AA8QQu4jhDyjvvYO9e/3A7gfwCtqPSctxlXQr487wDYwu9Q1Jw7gl40ZlqRFkHFPCyI7skkkEolD1GS4vwHznccA/B3YRuz7YAlybrCj8TPAbAgnAfSoX7+RUvoG4WfdBOAuIcnsTQD+Gsxy8EowpXoV2AP0KbBKAx0APkopfSMhZAPYcfz3wBKwtoAFckfBbA959ef+HQAvpfSTpt/FDQD8dS931M/2LuG4WiKRLDHqVb2hBDWR5MeUUkt1jhCyGsDXwY4MfkMp/afFGptEIpFUwZcBfBLAMQC/Bgs0VwN4Qf1+AMzycD+A/QC+COC3AP64ws89D2yNTAP4CSFkSv36mwH8CizAPgDgICHkOTAf/AqwxLTnARyjlB5WKzZ8nRCSByvHtQHA02o1FBEFzDp0a7UTsBShlN7Q6DFIJJL6sijVGwghbQC+BZagZMefA/gEpfRcAFcRQroWY2wSiURSLZTSJIBvAvgzAATAtymlvZTSXrAyew+pXtxdYIrtxQCeqFAxgQAQj964j/SbAD4CYBLMu/tdAOepa+UjYMlpnwVLdgOl9FFK6XZK6U4AD4IltZ1FKd2pfm0XmL93B6VUBrwSieRlw2KVLCuAqRUzAFN9CSG3EkIeIIR8XH3NOIDTVEXYC1abVSKRSGwhhMTUteR2taOflxDy/9S15R+E1/UQQu61+PdbCCG3zfPtvwLg7QDuBnANIaSXEBIBsyJsIoSsB/AH9b+PAegFsyfY8QiYX92n1tNtBwBKaVG1IDwH4FZK6TOU0mn13+wDExTeSSn9rvB7+QghX1Xf8ywA96ne4hcA3AvgflmyTCKRvNxYFHsDpZQHu/xLHwfwQ0rpTYSQhwkhN4Id//0F2DHhnWDldCQSiaQcbwXwBUrp7WqQdz0AhVJ6HiHkvwgh6wCMweKkSU36+gLmWbqMUnqEEHIPmJ/2n8BUVTeA/6CUPqm+x71Q6+KClTo7VeZH/gCsosJLAB4HoDXOIIS8Aaye7FnquC8Ga9byEoC9YLWITwNrqnAMzGN8O4DXC97eL4Mp0P87n99XIpFIWp1FTWQjhNxFKd1NCLkVTMVIgdVJ/COwY7trKaWUEPIlAL+ilM5XgZFIJC8zCCE/BhAFCzp/Qwi5DqyE0E/ArAO3qOWp+OvfDZZkdpX49WaDEHIhWMLaKymljxPWEONVAP6RUnovIaQTLMg9G8D7wQSEs8C60X0KQFr9UT1ga+4M2HyEwcqatWxXOolEIqmGRUtkM/EC2APoTkLI2wBMAOgHsJwQMgKW+SzLxUgkEkcQQs4Fq2V7BKwLGcCCu7UWJ00ghHQAeBtYEtpViznWalED2/WU0ln1758HK+nHvz8G4ApCyCYAz1OmZPxW/fbPF3u8EolE0qw0qg3xZwD8jVov8mqwlo//B6zzED+eu8P2X0skEokKIaQdwH8CeDdYEwbefS0M+zXuMwA+rjZ6aHp4wFvhNXuprEEpkUgktiyq0suPENXjtFeavv1r9T+JRCJxhJqMdTNYAHuUEPIYWL3chwCcDr2MmJmLAaxT1d/thJBPUUr/wea1EolEIlkCyOYUEomkZSGEfADAp8EqJgDA/4CV9/oDgGsAnMMrHfCcAoufYfl1iUQikSwtZNArkUiWFGpd8CsA3COTtCQSiUTCqXvQ29nZSQcHB+v6HhKJRCKRSCQSyWOPPTZGKbVscFZ3T+/g4CD27NlT77eRSCQSiUQikbzMIYQctfteo6o3SCQSiUQikUgki4YMeiUSiUQikUgkSx4Z9EokEkmNSecKODBSsbSuRCKRSBYRGfRKJBJJjfnho8fwyi/dh3Su0OihSCQSiURFBr0SiURSY6aSOWTyRcxl8o0eikQikUhUZNArkUgkNSZfLAIAkhmp9EokEkmzIINeiUQiqTH5Iqt/LpVeiUQiaR5k0CuRSCQ1Jl9gSm8iK4NeiUQiaRZk0CuRSCQ1JldgSm9CKr0SiUTSNMigVyKRSGpMociDXunplUgkkmZBBr0SiURSY3gim7Q3SCQSSfMgg16JRCKpMdLeIJFIJM2HDHolEomkxuj2Bhn0SiQSSbMgg16JRCKpMTmteoP09EokEkmzIINeiUQiqTF5aW8AADx8aBzvvulRTfmWSCSSRiKDXolEIqkxeVm9AQCw5+gk7tg3Ipt0SCSSpkAGvRKJRFJjtOoNL/Ngj9s8+P8lEomkkcwr6CWExAghtxJCbieE/IwQ4q31wCQSiaRV0ewNDSxZdnIqhe89/FLD3h8AsnkZ9EokkuZhvkrvWwF8gVJ6BYAhAFfXbkgSiUTS2jSD0vvzJ0/g//vZMw21FmhKb156eiUSSeNxz+cfUUr/S/hrF4CR2gxHIpFIWh89ka1xnt60WjkilS0g7JvXUr9geL3irFR6JRJJE7AgTy8h5FwAbZTSh0xffx8hZA8hZM/o6OiCBiiRSCStRq7YeHtDWrUWpHONC7wz0t4gkUiaiHkHvYSQdgD/CeDd5u9RSm+klO6klO7s6upayPgkEomk5Sg0gb0howa7mXzjgl4e7HJvr0QikTSS+SayeQHcDODjlNKjtR2SRCKRtDZ6IlsD7Q05Fmimso0LOGUiW+OhlOItX38Iv312qNFDkUgaznyV3vcAOBPA3xNC7iKEvLmGY5JIJJKWRlQ4GxXwcYU33QxKrwx6G0a+SPHAwXE8dnSi0UNpaY5PJnHlv9+N4Zl0o4ciWQDzCnoppV+llLZRSner//2w1gOTSCSSVkXsQNYoiwNXehfD0/vPv96LG37xXMnX9Tq9snpDo+C+6pnUy7tm9EJ5YWgWLw7P4YWh2UYPpanJ5ot4/KXJRg/DFtmcQiKRSGqMGOQ1yuLAld7UIrz/k8em8ITFg05LZJOe3obBvd0z6VyDR9La8Pv45d5wphK/eeYU3vDVBzAy25yKuAx6JRKJpMbki0WtTFjDld5FCDgz+aL2fiKyI1vj4dYSGfQujJRaiWW2iYPeQpHi2ESyoWOYTuVAKTCdbM7rTQa9EolEUmMKRYpYwAOgcUGv5uldBKU3my9aeod5Ipv09DaOTE7aG2oBr7ndzErvrc+ewqWfvwsTiWzDxsDv+WQDk3jLIYNeiUQiqTG5ghj0Ghf/x1+aRLFYf4+rrvTW/+HDlN7S99GaU0h7Q8PQPL1S6QUAHBqdwz/e8mzVpfySqtI7l7YOeimlDZ/j8bkscgXa0GQ7vsGVQa9EIpG8TMgXilrQK7YBPjQ6h9f/1wO4e3/9m/ZoSu8iJLJlK9obZCJbo8hqiWwy6AWAe/eP4dsPHsUPHjlW1b/jQdycTcOZ3z03jHM+/YeGBr78fptMNk7p5ZusVK45FXEZ9EokEkmNyQv2hqTwkOTHjosRgCxmnd5MvmAZXMs6vY2Hb35m0nlQKjcfefWU5ct3HqgqyVMLem2U3lPTKSSzBYzNZhY+yHnCVdapBvpppb1BIpFIXmbkixTxYKmnlz8IMhaqaK3histi2Rsy+WJJUJWdRyLbdx48gvv2j9V0fI3miZcm8b5v70G+AcE/vw4KRdq0gchiwj+D0dkMvvuw895afPNq5+nlwd5cAz2/uTy7/6Sn1x4Z9EokEkkNoZQaE9mExT/FWwMvQvDDS1Uthr2BB1YZk3d3PolsX77zAL7/yEu1G1wT8OiRCdy2d7ghwYjop26057QZ4Ervqs4Q7jvgfHPF72O7oJbP86yNErwY5DSlt4FBb2HxSiXOBxn0SiQSSQ3hD9Wwzw0XMSpDKU3pXbxAtNZB71wmj8eO6jV5KaXaA9/8XmJnOqeksgWMzTXuiLgecGW/ESqgmLA1LX29WovwFe1BjMw4v85SFYJefq03Q9A7Ke0NtsigVyKRSGoIf6i6FRdCXrfhIckfBPUu4VUoUu09rBLMFsKP9xzDm7/2oHbcK/4u5vfiCWzV2BvS+SLGKyiiJ6ZS+OZ9h1vGo8rnyFzJYzEQ1fdmK1t2ciq16O9ZKLL56Iv5q2qgwDevdkFvRgt6GxhwNkEimx70Nte1xpFBr0QikdSQnPpQ9SgE7WEvTkzqD3bN3lBnT6+orKZzBewbmsGl/3YXTk0vPMiYTeeRF/yh5veyGofT6g3FIlONxysovT9/4gQ++au9GK1x0lC+UMTQdO3LPTXS72kMeptH6X38pUmc95k78OLw4rb1zRcpPApBT9SP8UTW8YYsqXVks964NIOnl4+hoYlssmSZRCKRvHwocKXXRXDemg48eHBce7Dyrk5m72utEYPPVK6A507M4NBYAr97dmjBPztXMFoZxN9FTJqjVFebndob+L+fTObKJn2NzzEla6jG9Uh/+sQJXPJvd9Vcpco0UP3KNKmn97i6GTyxyGpvvkihuAi6oz5QCsdWGv7Z2dkXmsnT2xxKrwx6JRKJZMnDlV5FceHi9d2YFTywVupoPciY1Fce7Pxh38jCf7bJNmFUevU/i+quUzVN/PcTZR7cEwkWqNRalR2dzSCVK9RcKePBf0OUXmED1ExKL/cXL3aQmC9QeFwu9ET8AIBhh75eXekt7+ltaPUG9Z5rpNKr1emV9gaJRFItB0Zm8Y17DzV6GJIq4J5ej4vg/LUdcLsI7nqBNaPQ7A11LiNmVHqLWmDx8KEJy4f2iakUvvOQs/JNvCySpdIrvK8Y6DoPevV/z9VcKybUh3qtO0/xALHWrWb5xqARnl7Rcz3TQBXSDA/A7erecpLZfE3vl3yxCEW1NwDOryEe9KZyBctTCF3pbby1QCq99sigVyJpYn72xAl86tfPL0rZKUltKBT1RLaI34Odg2246wWmsKYaoPRmcgUtwMgWirjfokzTL548iU/8/FlHx988gOWBiJ2n1xj0OvP0iv++3LGzpvTWOOhN88ClbkFvI5Re9t4Bj9KkSm/5Mf3xNx/Bp371fM3eN1+kcKv2BgAYcegLT2bz8LlZyJSwCOiyzVC9Qb3OplM5bR1abPg8pJr0mSWDXomkieEqSDM9rCTl4cGe20UAABev78a+oVkMz6T15hR1D3rZ+4R9bs3e0Bn2IuJz4w4Li0O6CoUzZ7I3iCqcaE8Qg2GnQX7KqdLLPb3TtU1kq7fS26hENq/iQjzoaSpP73TSmb3h5FQaB0fnava++UIRbpcLHSEvXAQYcbBxyuaLyBWoFihbfY7N5OmltHHl6aTSK5FI5g1XFKZk0Nsy5DWllwW9G3rDAFh5Jh7U8QfDZCJbF0WGB5+xgAepXAEzqTzaQ16cvjyOfUOl2fKZKpRIc01eMaAVA2DxWN1piTYxaC6r9KrHt06OpveenMHHf/o0ig7mmc9DpSP3atEz2hc/IMrmi/C5XYj6PU1VsowHZZU2Apl8sewGqFp4IptbcaEz7HN0DfETmm7VB2x1n2TV04xm8PQCjbM4yKBXIpHMG764NjIxQVIdWp1eF1teI37WmW0mndebU+QLyOaLuOhzd+IHj9a++xgPPuNBD9K5ImbSOUT9HsRs1D5diaz8oDLX/zVaKazVXaeeXjHpyq5WbzKb197bib3h3v2j+P4jxxwFATyQr3XgUs381ppMvgCv24VowN1cSq8a9FYaUyZfqFi3uRryBVayDAB6on5HiWwJdbPSHWFKr5Wam1XvuWbw9AKN68qWNVWqaTZk0CuRNDFzWtDbuMQESXXki0Z7Q1QNemfTOU3py+SLSGTymE3n8czx6ZqPgQeFLOhl9oZowKOqfaUPZR4kV2dvsPD05kVPb/XVG4z2ButghLfyDXkVDDuo3pArOFeeMnWyIVQzv7UmIyq9TRj0VrIDZPJFTCazjpR6JxRUpRdgQawTT29SU3pZ0Gup9NbplKAacoUi4kG23kwmGmtvsPI9NwPzDnoJIT2EkHtrORiJRGJEU3qlvaFlyBWM9oaI3w2APdxTQpmvpBrgHRlP1HwMmtIb8CKTL2I6lUPU70YswI64zZ3M5mVvyJdWorBNZMs7TWRj/8aruGyPtHnQe1pfFLOZfMUxi35aSin2npyxfW0181ANjUxky+aL8HkURAOepmpD7CSRjbe4LhRpzcaeLxbhUVjo0x31O/L08s1qt1rxwdLT2wyJbIWiFpg32t6QWkpBLyGkDcC3AIRqOxyJRCLCSxzJRLbWgXt0+YM1GlDtDamcoTkFfygcGUvWfAyap1dVfUZnM4j4PYgG3MgWiiXtgnV1xonSy0uWldobxJ8rft25p5fNSX/cjzGbI21+1L2pPwqgssWBey2T2TweODiOV3zpXtsuYPz9a129oV4KsrP3LsCruBD1u5vK0zvjwNMrXjfjidokLeYLutLbE/VhPJGtmGjJld6uiH0iG9/YzWXzNVOlqyWbL2q+40ZZ4sRGLM3YJny+Sm8BwJsB2G+ZJRLJgpmTnt6Wg9fw5A/WkFeBizAFSGxOwQOsoZl0zVURXellQW86V0Q0wJReoNRHyV9fnafXWZ3ekFepunrDsragrb1hUlB6gcoNKkQ/7cgse+2JqRSmUzm84ov3Yt+Q/hirm9LbwNasmXwRPo8L0YAHs+kcvvPgkbJq92JQKFJtY1FOGRWvrbEaJbPxkmUAtFq9oxW6siVNnl4rC0NWqJzgZPNYD3IFiraQF24XabjSW6T1r1IzH+YV9FJKZyiltkY0Qsj7CCF7CCF7RkdH5z86ieRlDl88p1LS09sq5DSllz1YCSEI+9yYTecMzSlE/+rRidpaHMTqDZyo36P5i81HxfOxN2SsPL0WiWxBn7vq5hQD8UBFe8MmNei9Z/8oPvC/j9kek/P3TmTyWrAymcji4Ogc9p6awfOnxKBXDf5rXb2h0fYGtwuxgAdFCnzilufwn3fsX/RxiIgnV2WDXrFDX42S2fLFItzc3qAGsZUsDvzErWz1BuE+aFQFh6xWns6LyQYIJbz1eFS1dDWjxaEuiWyU0hsppTsppTu7urrq8RYSScuSyRccdwGS1Rtaj4KWyKYvr0xlyxuaU4gPhFpbHMTqDeIYYoLVQkQrM1RNIhsPftX/exRiSmRjXw9XEfTyn7WsLYBUrmBZ4ms8kYVHIVjbzUrBfe3uQ7j12SFb9VIMerm6OJHIakG16DfmQXutqyw0vE6v24XX7hjAJ161CZv7ozXvZFctfNPVHfGV3WCIfnE75b9aRHsDr6xS6XPh92os6IHX7bJ8fSavB3uN8vXmCkV43QTtIY/WwGUx4Wp3POgFAC1voZmQ1RskkkXmOw8exRVfuBuFIsX4XAZfuP1Fy1qtmXxB8082UwKKpDz8M+MPVoA9XMcTWa2GbyZfNCi9tU5ms1V6A+WVXifBnl31hljAY2lvCHoVxx3ZUtkCCAF6Y0xRs1J7JxNZtAW9CPncWpIgYF/iTFRZeYA1kchqQYHoG9VtHrW937KFxim9mXwBPreCzrAP77lgFdZ1hyse59cbfv0tawuoHnPr6048Hq9V2bJ8US9ZFvQqACorkvzELehREPG5rT29hSI6wvYlzRaDXIEl6fVE/RhyUIqt1vB7rU3dbDdj2TIZ9Eoki8yp6TRm0nlMJLK4be8wvvSH/dg/UppYkxACEBn0tg68Ti9PZANYBQeurhHCHubig/5ojYNeXpvV71G0rznx9DorWcYT2YzVG6J+j+E4mgcsIa+7qkS2gIcFaIC113I8kUV7iClJ771gNT5+zUbt61ZoAWe2oAUrk8ms5hEVVWg+/kSdlN5EtrDoSU7c3sBhFQsyDU0y0oPeIAD7IFG8nmrVoII1p2Dzwe+PSi1zuRc76FMQsgl6s/midl02qlZvrkDhUVzoi/kxNJ1a9PfXNsBc6V1q9gZK6e4ajUMiednAj2zH5jIYVWtEWtVUFAOQpW5voJTWzLPXaLQ6vYqu9Eb9Hq0eaCzgMdgb+mP+2tsbcizQCYhBr9+jHb9OJ63tDXMOlBm9I5tefs2jEAS8iknpZUFVyKc49/TmC/B7FLSpwYNVfepJIej9y8vX4d0XrAJgf/xt5ellSm9p0FvP5hRcXawUYNUabm/gdEd8yOSLmGlgaS1R6QXs51u0N0wksjgwModnTyysrnWhWITHVZ3Sm8zm4XYReBUXwj63TUe2IjrU67Jhnl5V6e2NBTAym3F839Xy/QE9gXbJBb0SiaR6uIpkCHotHu5iF6Cl3pzi3v1jOOuff4+TU4uvTtQavSObGPS6tSArHvAgWyhqxds39kVrbm/IqMGjUenV7Q3mgCdThafXqnqDV3HB53YZPL08OA753I6rN6RzRfjdLi14mLDYDE4IQS/AFPVYwGO7aRLbonJP72QipwXJovWiHqXFCkWKfJGiTVW/FtviwDdAHF52a3S2cb5eHvQOqEGvnTLKPztC2Hr50R8/hY/c/OSC3lv09PJNYaXgLJEpIOBVhKRU42dYKFIUihQdYa70Ln7QSyllnl6FoD/mB6Vw1HijlvDPK67ZG2TQK5G87OEPvYpBr/q6gbYAZtJ5S9/vUuHF4VnkixSHx2rfqGGx0ZVeYyIbhyd58Af/aX0RnJpO2/oa50OaK71eUel1w6O4EPQqpZ7eKo71zYlsvPmB36MYqjfMJ5EtlSvA79WV3kmLQHbcFPQCQEfYa3v8zYPaOVHpTWY1OwR/UFNK9aC3hkEL//ntDVIBs4UifG79OuBB72IHRCKO7Q3q3HWFfTgynsBTx6ZwZCy5oLWQeXrZvcnvj0rqeypbQMjLTkkifnfJ/cOvb76xaURXtkKRglKoSi/zxC+2xUELetX1rlGl28ohg16JZJHhC8HYbBZjc9zeUPrA5klFA3GmhjSqQcUd+4bxtm88XFcvIve7Vqq5KvLsiWlDualmgSereQyJbHrCFVdBppNZEAKs74kAAI6OL8ziIHo0NaVXCHZ4pjrrymayNxScK5y6vUH39HoVlxr0WiWyuZErUEce0kyuAL9bQcirwKu4MGHaDPLOXDy44HSEvLbNC/QauXnd0ytWbygYq1D43C6kcoWabTL15B6u9C6yvSFXMNkb1Nq0DQx6Z1I5eN0udIbLe2D5Z9IXD2B4JoMiZZ/nqQUEc/lCUVN6fW4XXMRZIhu3QpzWF8X+kTmDYp8RPmNCGuPp5de5x+1CX4w9M05VsZ7WgsxS9/RKJJLqMdgbeNBr4dnVlF416G1UK+L79o/jvgNjGKtjCRyeaVypu5bI3/74afzfXz5XryHNm7xl9QYh6BUqKAQ8ClZ1ssaWC7E4jMyksfETv8UTL00C0JVev4cn7Li0wCfqL21Hy2vuOuvIVlqn1+dh7yUGvVoim09R/13lIDKdK8LvcYEQgraQp2QzyBW5sM9t+HpHyFfR3jCXMSayjWr2BmPQW2tfZqbAxuxU6R2by+Cnjx+vyXsDanMKQyIbr01rfz//4flhnP3p31uWjKsF06kcYgG9brS90qv73kUWskEUm1MQQhDwKBWDs1S2gKB6He9a1Y5CkeJx9V4D9GvM73Eh7HXXvKOfE3jpPaPSu7hBr9nTK+0NEolECyxGDYls7IG9b2hGU8TmBHsD0LgKDryLVT0XUK70Oq0fmi8UcWBkrqFHtHbwIMpgb/CX2hum1KB3Zbsa9C7A2nF8KoVMvoj9w3MABKVXVafE948FPBbVG5zZG5hvsLQNsVdxwe+2tjcE1WNhJxaHVK6g+ZDbgt6Sigz8IcqDeU57WXuD7lfmwVWR6kon/314gMXLTtUq6NWU3hBP7in/c2958iQ+cvNTjtTM2XQO9x8Ys/0+9xOL9oaIzw2f26Xd11YcGJnD8EwGxyfrczzOg96IUNd2//Cs1s2Qw203/erGf2MvOxVxaoNK5wp42zceNnTdyxeoIck04HVXtDcksnkEPWysZ65sg4sAjx6e0L7PrzGv24Wwv9TzuxhkhTFE/W6EvApOTtl/xk+8NInX/9f9jq7zdK6AR4Tf13YMJde6DHolkpc9XME9NpHUFoXJZBbPnZzG1f9xLx5WF5cSpbdByWw8OCi3gC6Uau0NRyeSyBaKjssYfeTmJ/E3P3qq7Gsopdg/XFo6rloKpo5sgG4tAPTauVPJHAJeBbGgB21BD44sQL1KqsEq3xhpSq8a7Iie4mjAjemU/qDjgRFQOclKLD3Gk9a40uvzKIZs+2yeHSPzANVJ0MtLlgFMGTUrvVxJFhP0AKAz5MVkMmtpScgJ1o25TA49qtJp/j4PsHgyUq0SzjRPb9CZ0suTCZ2omT974gTe+o2HccCi5KH43qK9gRCC7qiv7IaRb17qlVjKg96Qqtg//tIkrvyPe3D73mHD6zR7g6pcXnfmMvjcLscl/o5PpnDfgTE8dlRXZcWSZQCr4FCpnqyo9IZ9bmzuj2nrNKDPs0dxoTviw/6ROUfjqyVa4K0QEELQG/NjaMb+83vmxDQef2kKD5TZNHF+/fQpvOlrD1bciPF5iPg9IETW6ZW0CJTSJZ001Wh4gLJvSH9QTSRzODjKFnK+sCSaROnlQe9CfHTloJRWrfTy4HQ6lXNUGWDvyRk8dGi87Gtu2zuMK/79Hry0QG8tDyDt7A28cPuMqvQCwGBnaEFKL1cPuYLLlV6PQuAi0EqVASwAFj292Sq8rKJFwVy9gdkbjEqvV3FpSUNOPqe0qPSGvCWeXrugtz3kRZFabwz5+86kckjniljRHjT9TlyxVpXeUG0bDJi7VFVS07nq+NJE5euQlzK8zRQscvjvJNobAObrLefp5RsaK0/odDK34Bq/POj1KKys3u17h0EptBwH8/jPWtWOTX1RXLO1D4MdIRx2WOKP3xfiMXu+WDRsSAMepazSSynFyGzGcFpy1qp2PHlsShufqLK++vR+PHVsCi/WYANdDfw65vdbXyxQ1tPLN3kPHCy/LgK6ta7SJkhcS5zYRhqBDHolJXznoaO46F/vbGjx8qUKpVSzN/CHajzIvIt8QeEPsrlMAR6FoEs9bm1UrV7+cKyXvWEmldeCpWGHXYReHNaVFCf1fWdSOZyYSpWtkMDrf55cYHCvPXxc5as3TKVyWvb4YEdoQQ0q+MPFrPRyz2LU1JlNDHr1YI+N6+h4Ah/78dOWc5UTSkiJdXp5IwxznV6PwmqbAnDUoCKdY6oxwJTRUqWX/YyAKejllgSra4EH6lzZXF4S9BrtGp31UnpDzn4u/yyPOQh6+VpiVkjN7+3zmIPeSkqvMeg9PsnGMjqbwa5//j3ufnG04tjKMZXMaQmdEb9bL5lnCpL419d2h/Gbv7wQA/EAVnYEHd8rfIMhBr0FoWQZwCo4lAvOnj0xg1PTaVywtlP72q7BdmTyRW3N0BR1xYXX7RiARyH44aPHHI2xVpiD3t6Yv+yazT/jcvYY82vL+cABY/Af9CpIZAs4NLr4qnc5ZNBbJ37x1El8495Dtt+/fe+wI49MI3j+1CxOTKUa3qpyKZLOFVGkxqPv9T0RTCZLg95EJo+Qz60FLI0IelNCbdOTdQp6h1Vv4WBHEKNzGUenDKKKYlaHrJhO5UBpeS8g98MudJ4LRQoXAVw2Sm8sqCeyccVysCOEkwsoW2YOernSCzBVVFSpogEPZjN6CTwtKFODvVuePIkf7jmGvRaVMfhDLex160qvWhLL71aQL1LNl8maIija0bqzRDbd3tAW8mIqlTNcD1yRE0uxAXrAPmZhd+Fj5go891Cbv697emubyGauXVrp5/J5dWJv4KdGT7w0hRGLU5KMEIyJdEV8lq/Xx8D+3ampFB46NI4LPnsnXhiaxbFJZitaiNWJUorR2YxWOk28N8zBZ9Zi/Ks6Qzg6kXRUTSaVU5XenKj0UkO3xIBHKZtw9ZtnT0FxEVyxqUf72tZlMQD65lsM9jrCPly5qRc/ffy4we5Tb7JCIhvAkv+GZ9J49MgE7ttfGthyNX//yFzZawHQk1YrncSJn1fAq+DHjx3DpZ+/G08em6rqd6knMuitE9964Ai+ce9h2+//86/34nO/27eII3IOL9perySGevGrp09iz5Hm3Ehw+AOP16cEgPU9Ycym89pDjgcuiUweIS+rrRr2uTFRoXrCyGwaf3jeWvGZL2KyyymH/r5svoj3fmsPfvKYswx0rkacvjyOQpE6CmL3D89pNoFKr88LjSAOqRaSfKGIN3/tQfzLb57XFuoDozzoXZh3OlegcLuMSyt/sLtdRKs8UChSwd7ArgcnR9pW8GNcs9ILAK/c1ofdG7q013JP8axmhTCW1HruJFOvylkFuDpHKdVKYnHvLq/fywvl84ewU08vD9Y7Ql5QarT1pDR7g3F+yym9ZlvFio6A9ue2oEdTr/lxb3uoPolsAY+iHvlW8I9WYW9IqJ3CAOB7j7xUWpWD2xtMynh3xIeZdN52k8WDnKGZtBawHB1PYELdVIj/7v4DY7j6P+5xnKk/k8ojWyhqJ1hhYUNmthlk8gUoLmJICl3ZEUI2X8QpB1YoTek1BL1Fg9Ib9NrbGyiluPWZUzhvTYdWOxrQ7UK8Hq85OH/djgFMJnMGL3G90ZPp2O/WGwugSIHrb3wIN1hUuRFbPN9/sLzay+9p8+lAOlfA+769RysdKXrIO0I+bcNa6zbrC0EGvTVkLsMWEUopy36dTdvu9EZnM9h3anbRLQQ/e+I4DlQw2fOMaSfHa83C+FwGf/H9J/DGrz2If/vdCzWd1/d/5zF89a6DNflZ/IG3soMFOYQAa7rCAIDnTrKFgwcbc5m8FiBt6I3gmQrtN7/9wFH8ybf31FRd4NaGjpDXcc3HL/7hRfz++WHcs9/ZEShXD7YtiwOobKPIFYo4NDaHc1Z3AEDFZDax+xg/ahuZzeDhwxP42j2H8JavP4R0rqB5aq3Kx1VDvlA0ZIcDevWEgFcx+CsDgtILzL+CA3+4c9tCRggeP3ntFrz+jGXCWNzqa9m8mO0Nz57g12HpPPAHKz99yOSLavMDl/Z+PCDKFYrwuF3aqUYlTy+lFOl8UQto27SubPrnW87Ty15bugHKFYxBTlfYr71HT9RfWrKMK7018vRmhEAg5HPj5j3Hsf2Tt9kmn6WqsDckMwWs6gxhTVcI//H7/dj1qd8bPOli7WERXqt3//Cc5VrJVcCTUym8qOYejM1ltVrIYue9505OY9/QLA46PMbmJ4hc6Y363YgHPYgHPSUbAnM3OUDfIDq5V6w9vdTQLTHgtVd6nz81iyPjSbxia5/h67xRBd8YmRMG1/WwNf1EBeHor29+qmbPlhJPb5x9xnZCQjpfQJs67/cfKO/rTWtKr/HnvDg8i9v2DuNhNV8iIyjeX7p+B375oQsANLYmtJmXZdB7574RQ429WkApxRv+6wF8/KfPYDyR1Y5TT1kcA6WyBSTUY+PFVFPzhSL+5kdP4+v32NsuAP0hc3wyhQcOjOGcT/+hJklUU8ls3Y457tg3giIFLljbiS/feQCPHqnN55vM5vHb54bw2d/uw3cfPrrgn8cXyZWqr7Aj5EWnqnjwhYknDSSzBa3G6c7BNjxzYrrs8ffwTBpFWtuEN76zP315HMMzaW3nfv+BMW2hE3nipUltEa8UjE4ls3jo0LgW9J6uHhken0zhOw8dtX0QHR1PIFegOG+NGvRWUMBF/+oh9UHJ53r3hi7sOTqJnz9xQjv+nkotTOk1P1QBFqR51aQdsXyU6OkF5l+rN5kzKb350mCBExPqBAOC0qsGjrxWsnXQy+aIK9fpXAGZXNGo9Ar1e72KCx63M6U3V6AG9ZtXOxC7FdoFvW1Bj9qq1srTW9TqhgJA2O9Ge9CLiN+NkM9dUrKsU1V6a+XpFYPeLQNRxAIeJLMFfOsB6/WEq47jiWxFtTmRZRaon/7Z+fjHV21CtlDU/Lfm9xbhvuZXf/k+/Pn3nyj5uZq9YTqNF4Z50JvRBBExYZH/2WkZMR4AcaX3AxevwWdevw0hr9vS02u+jpfF2didVJbgP4/PKe9aJp7ElEtk+/4jL8GjEFwpWBsAZl0KeRXboLc35gch5SveTCay+NkTxysm2Dolawp6z13dgX981Sa8+/xVmE7lSsrBpXNFBDwKzl3dgQcOjJUVijRPr6nMHd/oJIV7HgB8ioIVHUFs6ovCq7gs78tG8bILerP5Iv7iB0/gQ997wnFrTCc8dGgCLwzP4sGD4zgoKKlWQa2461rMjlIjs8wv+aKNwsAZ0+wNSdz14iiGZtKOzOiPq3X/7I7vvnzHAbzhqw/UJSHq988Poy/mx1ffdiZ8bhd+/fTJmvzcI2qWcHfEh0/8/NkFl/DhizB/6HSGfSUtVfVEtrxW0mfXynbkChRPldk0aEFzDb2//AG1bVkMeUEx+IefP4u///mzJa//9oNHEfF7cN6ajoq2g+8+/BKuv/Eh3PPiGOJBD1ao6veX7zyAT/z8Wdz1wojlv+MnFduXt8Hnrryg8uDORXSllwfk7zp/Fdwugq8JG8GpxAKV3mLRcBzLiQbcCHoVQwDCg7eYqrjMt2yZXrIsD0qp1hrYCq7SzpjsDe1B83VYzt7AfkY6V9Ta3OpKr25v8Cgu7ci3kqeXq4d69Qb2HuLmiT98zYlsbsWFeMBTYm8oFlldYe6jBljJqTZ1s+lRiBYs8HGHfEyNr8becGIqhT/+5iPW9oqCrrbe9K6zcM/fXoJXbe3Dz544YRlYi5u9SpVE+MY4FvDg7NXtAGBojMCPsM2B4zmr2/Gj95+LyzZ24w/PD5cERHwMyWwBL6hK7/hcRvssMkKQyD8Tp6cUZqX3vLWduHpLr1o6rNTeIG4SAX2j6MT/nhR+D0BsEW60N1glso3MpvHDPcfwhjOWafYZkbDfrX1+Yp1eAPC5FXSFfTgxZf/53XdgDEWKkprZ88UcePs9Ct59wSoMdgZBaWlzo0y+CL9HwflrO3FyOl127eH3xshMBkfHE7jwX+/A4bEEDo6wz5yvP+YxEELQEfY6sqwtFi+7oPfhw+OYTedxYiqFX9UgMMoVmK/tB4++BICpJPcLJUDEXTdn1BD0Ll5ZE15y6oDNkRbAFhleVeDYRErz9zlJXPjmfYfx+EtTtjv+R49OolCk+EkNuw0BbPG758UxXH5aD8I+Ny7d2I3fPDtUk7Jr3Iv0kSvWo0hZwshC4IskV/a6Ij4twQVgnjAebCQEe8OZK9sAAHvKeMRG6xD0jsymobgINvczFfbUdBoz6RwOjyXUAvb6dZErFHHHvhFcdlo3VnaEKi50/Pd85MgEeiJ+dIZ8cLuIthE0l6vicJvFQFsAnWFfxffhQe+G3igOjSZYIo36b1Z1hHDO6g4cHkuAEGBFe3DhSm+hVOkFWKAY8Lot7Q0AuybmbW/gJctSOVvfK8es9JoT2ThWHQB5ABc1KL0F+NwuLTgxlDJzOy9Zxv8dD9b5ZlBUevXmFKUBfUfYV6L654pGvzLAVOrVXWGs6QrDo7hKSpb5PAoifrcW9O4bmtGy9O2498VR3P3iKH5vUUVB93vqY37rOSsxl8njlidLn0GpXEGrJVzJ15vI5LXmHxGfmign2DL0gNs4X4QQ7Bpsx7U7BpDOFQ3lEwGjfYGfgIzNZbWgPm0Ieuep9EaMgaRV8JnJF0sqT+gnCpVFK77e8vHybolGe4N1c4r/d99h5AtF/OnFayx/dsind14zq6wAa6hR7rnJK2DUqr0831Sakxb5tW/ekKVzBfjUoBcoX8WBz8/wbBr3HxjHsYkU7nphRFd6s9ZBLwAZ9Daa254bRsCjYE1XCF+966CjDFA78oUidn/uLrz6y/fh1meHcPryOADgp48fh9/jguIi1kqvetO7SKnS+9jRSfz77S9WNY67Xxx1pECeUG/A2Uze1p85KahcxyaTms+0Uo3WuUwev1eTqKyUt3SugL1qAH3znmM4NDqHm+4/XJPA9IGDY0jlCrhcPYJ65bY+jM5malId47Aa9F65uRceheDpE1ML+nnceznQFoDiYuXIRKV3fW9YCzYSgtLbFvJifU8Yj5ZJ1OMPk1o2sRidzaAz7NUaZJyaShkCAHGh3HNkEtOpHK44rQddYS8mEtbNAjhzQr3SnpgfLhdBt/AgNJer4gzPZOBRCNqCHnSU6cTF4UrKjhVxzGbyGJ3VFavOiBeXn9YNAFjWFkBvzL9wT68pO5wT8bsRENoBA0DAq/95sCM47/aqPBjMForaz+C+TTN8I8UDAnul197Tqym9+YLg6XWpP0/39LI6vcTwb+1IZ9n3/er8WD2seUKNWekFWJBsvhZ4INBmUno/d902fPktO+A1BL36+3eGfVrA+dc3P4V/sDjVEOEB330WgYNVIHDGijg29ETw8ydPlLw+lStgQ28UQGVfbzJbQEhVPsN+o88U0BVZO6vLGSviAKC1r+akc0XN4w0AIa9ib29QP+/DDq05Y3Ps/o0JlhPA2ltr5ek1e8fLUar0ltbQDngUZPPFkrXq+w+/hGu29Gltws1EfO6Se0gMOAfaArbP5WKR6kFvjbzjZk8vh3+O5nsjrW5WBzuC6I/5cf+BMSQyrDOeeW7536eSOe1aefLYlBb08ioZ2QJLPBTntzPsc9xEaDFo2aA3nSvgm/cdLhsEmCkWKW7fO4yL13fhA7vX4sXhuaq9vZRS/PTx45hO5fDMiWmcmErh4EgCuUIRn3zNZngUFuiu6QqjL+a3VHp5UHj68jieHzIGvTc/egxf/MN+xzujfKGIP/nWnrKVIjhi9v2Lw7P4zK378H9uedZwgfP3Xd0VwtHxpPbgq6T0/u7ZIW0htDKtP3dyBrkCxTVbenF0PImrv3gvbvjl3poEpvfuH4Pf48I56vHepRu7EfAo+PUzpSrKrc+cwlu+/pDjYPvIWEKzIGzojVRUfCrBFbmwz43X7xjApad1G1SozX0xTKdyKBapIZENAHYOtuMxVS03UyxS7bqqrdLLSgvxjkgnp9N45vi09juID/nb9w7D63bhovVd6Aj7UKRGlc7MXCaPeNADt4ugL8p+/sqOEDb2RhDwKLbB58hsGt0RPwghbEE1qXu3PTeE13z5Pu0hwBXNM1YwtfzgaAJjcxkEvQqCXjcuO41tltZ1R9AW9GC6BolsioXS++pt/XjF1j7DQ5yrdABrUHFyunwtYTsSQrDAj6P7Y9ZBb1ANkrQHtvp+Ynb6QDxg+dmJ1RsAFvxwRbfU3kDhcRMt2KtUp5cHT/z42u9REPQqhs0PD4qsgri2oKfk2tfLhbHfjRD2+/s9itq8w4Vcntfp1ZXec1Z34NEjExieSeO5kzMV12PuFb//wBgKRYpfP31Ks3ll1d/L3BVt67KYpX0hlS2gJ+JDLODBk8emynotk9k8guoawf3/hqDXJpGNMxAPoCviw+OmE6xMrmAI9nYOtrOgd640kY3PWzVKb2fYB0KM90jQ69a86RxunRHxKExQSjtI2DUnsundEo0d2cTXAmzjNpPOY1N/1PZnh3zukuoN4jwPxAM4MZWy/PyeH5rB6GyGVdFQ16cv3P5ixa6R5dCDXuO88hMcs9KbUZNGCSE4f20n7jswhss+fzeu+Pd7sOX//M5Q5kys9MCD9ceOTmr2v4RgbzArzU5O4xaTlg16CQG+cucB3FghKUtkz9FJDM2kceXmHi1AeqHKrimPHZ3ER25+Cl+7+6DWyeT2j1yE3334Ipy+PI7T+thNsqYrjGVtgbKe3gvWduLoeNKwSPGFo5x3U+TUdBrZQlGrdVrptfyCfOTwBL5+7yF868GjeMUX78VF/3on/vx7j2s7+e1qJj3AFGm+Y6WU4r79pUlMtzx1UjuSs7rA+e7w49echq6IDxt6IvAoxNa3WQ3PHJ/G5v6YtjgGvW6ct6YDDx0qDahvf34YDxwcd7zZOTKWxCo1W3jrQAzPnphZUGUIHmiEfW587o2n41Xb+uFXSxl5FIJ1PWFQ1eeVEBLZAODMFW2YTedxeKzUXy3WM13I8Xwik8df3/wUfvvskFZPszviRzzoQcCj4Oh4As+cmMZAPIDdG7pwv5oAQSnF7c8P4fw1HQj53CXJeXbvtawtgJvedRb+/NK1AIAvXr8d33nP2awFrU3APDKTQbd6rXWEvBibNb7u6ePTePr4tHaKwoNenih3dJwFvTxLf3l7EG85ewWu3d6PeMD+fZ2SK9KS6g0A8CcXrcZ7L1xt6ekFmL2B0vlVTRHbffKNdF88YPlafnqQENRhQFdWQ14Fa7vDlgmRZqV3Lp0HpbCs3sAfgF6HJcu0JDUhyGkLGruycXXKZbGpaAt6S679nPa7sfGGfW5DsOVxC0qv4H89b00H0rkivnLnAQCVN5KHxxLwKi6MJ7L4x1uexQe/9zh+/zxb27KFUqUXUOuozqZL5iWVKyDgVfD6Mwbw62dO4e9//qztmpPI6EqvT62JLHaS04Mxa383IQQ7lsdL1sN0roAV7UG4CDsBWdEexHjC2t7A520qmbM9nRERa/SKWDWJyOQLJfMGMDXekb3BlMjGvcviptSvzp9oceBBXMhrPW8Au5bmbDy9APt8M/mi9kwV4Ta5yzf1IJMvIp0r4OFD4wtq+iG2QhYRK5vkCkXdy5/T/dLnr+3EbDoPxUXwyWs3I1+k2CcIcul8QbOEjMxm4Pe4cHwypV3bor3B/HlxpbdZml21bNDrcyt4867l+MPzwzhhOkL4yp0HcMMvjHXpbnnyBN71P4+gPeTFZRt70B8LwO9xaXU7nfLrZ06pP+8k7ts/ho29ESxrC2J9TwQAcLoaLLKgN2gb9Eb9bq1E0wuCn4orBk6rHPAjuFEHnaxOTqUw2BlEZ9iHbz94FIUixd9evQEhnxsUFH94fkSzUFm0IQAAUoRJREFUXnCrBiHAjhVtODWdwlwmj+tvfAhv+38P44Pfe1y7iFPZAh44MIbX7hhA0KtYKr1PHJvCQDyAFR1B3Pk3u/HzD56PXYPtuOuF+d3kxyaSePbENApFiudOzmDrQMzw/e3L4zg4OleSJMCTDO06GJk5PJ7Q/LdbB+KYTuVwbGL+yWx8cQj6jItpW9CD3phfCzyGZ1jSoagErulmZXCsrllxzhei9D55bAo/efw43v+/j+FdNz2Kk1MpdKmqzMXru/CzJ05gz5FJbB2I4fy1nRieyeDAyBxGZjM4NpHChetYPVje1arcsdZcminZF6zr1BL7uqN+zeds93sMz6TRox7dcx+nuKByNf1x1f88k8rDq7iwqjMEt4vgpYkkxueyWmAOAJ9+3VZcu30A8ZAHU6mFtVktFKihG5sZUQkxeHo7eQWH6oPeRKagqUz71DyBPhul1+dmSpmu9KrH+h4XQl4Fq7pClqopIJYsU8ueqfeXV207CujBA09kc1qn18qv2x4ydmUT6/iaiQU9mDS1yDUrvRHh5ASAIZEtk2cKvUdx4ezVHXARlr0PMPXUzpNcKFIcHU/gFVt7AbAETUD3alo1WACY55PS0oL/qSwLev/xVZvwngtW4XsPv4QnLJ4HhSJFKlcwrBERnxtzGbHbnnXALXLGyjYcHU9qKi7AbCRBn4LeqB8beiLoDPswlcxpm1gx4BSDxUNjCdtSbJzR2YxWuUEkaNEkwsreAKCk+58d/OelTPYG0dMb5NdtVgx62b0RMl0vImHB920VcA6otditypbxa3qtWq5yNp3HZDKL0dnMvEtOap5e03zxZ8p4Iosb7zmEq/79HgC60gsA12ztxQ2v3oRf/Pn5eNvZK0GI0XaRzhWwrE3fRL96W7/2Z49CBHuDVdDrRbZQ1EokNpqWDXoB4C1nrwAF8D2hlBSlFN9+8Ah+tOeY5tdN5wr46I+exvreCH71oQsQC3rgchGs6gxX1SKvWKT47bNDiPjdODGVwoOHxnHemk7Da7arweLabqb0Ds+m8fChcfz33XotvrG5DDojPq1WK7dAzKT1RaXqoLeMonbXCyNIZQs4OZ1CfzyA9T1hzGXyWNUZwgcuXoNffugCfHD3WqRyBTx1fMrwe6zqDGFtVxgnpljjg4cPT+DCdZ0Ym8tqAfpTx6eQL1KcvaodXRGfZdD75EtT2K76x8I+NxQXwSUbuvHC8GzJpqUSlFK87zuP4R3ffAQvDM0ilSuUBr0r4qAUePrYtOHfHVQDRtbrvXxgM6f6P3kwwt9jIb7euUweHoWUKC8dYR+WxYNaUhv3SonWh1VlylqJc262BVDKrltzhrYVvLLG+y5ajfsPjGEymdNU1Q9dthaz6TyGZtLYuiyGXYPMLvD08WnNR7q6K6T9PkB5pdds3xBpCxoV158/cQIXf+5O5ApFjMxmtFOFzrAXuQI1LND8gcWPbKdTOUQDHrgVFwbaAjg6kWT3oMWDty3oRTZftC1h5ARz8XszhBDtQW729ALzq9WbzOa1IPeFoVm0BT22wSEhrNwS34BlBDUwGvBgdWcY8aC14p3JG5Vergb73IpmeZgVjny9bqFkWb5S9QbVryvMyYqOIJ45Ma0FFSmhY5uZeIB9dmJAxgNafl+F/cbrTfT0chUZYMl+W5fFkStQcGHYzit/YjKlltDrxJqukBZQJYSAiJDSY2euxIvWsWKRIpNnpaQIIfijs5YDsK7iwK9R8TRIPHIHhOS8MkHvDnWtF5856VwBfreCf3vj6fjbqzdqpyJ6y2ajvYEr6X//s2dw+RfuwW+fHbJ9v9E5a6XXNpHNNuh1nsimK71q0GthbxDv+TnhRM4OUem18m33q3VyrXy9U6kcQl5Fm9eZdA4Taj7N8PT8rAB2nl6P4kJMrWzy9PEpnJpmpSfFDaTPreCd569CR9gHl9pAR0ywS+eKhvbd15+1XFvjNvZGNWXc6vPin3WzdHidd9BLCPl/hJAHCCH/UMsBVcOytiAu29iNHzxyTLvoDo7OYXgmg0S2gKNqQPjcyWlkC0X82e616BeO/FZ3hbQgyAlPHGMXzMeu3qgtvOev7TC85vLTevDmnctxwdpOLGtjpULe++09+Myt+7SjobFZpjLxhxRPKuMPu+6ID08dm3KUZMeDDbviz8cmknjn/zyKb95/GKem0uiLBTRV+pVb+7SjvnXq1x46NA6PQrChl/19c38M/fEAxuYyePTIBHxuFz7xqk0AgEdVPy7vOrNjeZulf+foeAInplKap5JzyUamCjq1OPzq6ZP45VMncce+ETx/agYTiazW6nnbMmPQy1V0MUFjaCaNuUweG3sjrNxKhQ0P/zy4t219bxgehVRsElGOpJBtLfJPr92CT7xqk/Zw3qPWGV6rqrsAU7Lagh4cHrPyibM59ygE06Yj3gcPjuP9//sY/rCv8jzzGq1/dfl6fP9PzsFgRxA71M3K5v6Y1opz60AMK9pDcBEWhPMqFyt5VQo1oCxXlFwsyWbGrPQ+cHAMR8eTeGFoFtOpHLpVD7CVjYIfafIj25lUDjFVmVzRHsRL4zzoNSZuAdDquS5ELc8VaEmAY4Y/HMUALh70IhbwzKtWbzJbQF+MrW1DM2ntz3aEDA9s3XP6hTdtx0euWI940IPZdL5ko2Su08sfjF63q7QqhCmRLePQ3iBuCK87YxnG5rLayUw6VyxpQczhgZdoceCBQDzAPmtzEMOqN/A6vcYHNq8DvWsls8LZVRM5pNqNVnWF8H9evRn/+Uc7QIjgmVbnwexh7dfWfz0o0tosq9cFf15ZCQNJ9eeL64kYiPHfCUBJBQQRHszwe5VSPSA6b20nNvRGSjaI5qB3XU8ELgKtCsRX7zpgKSoUihQTiazlhjPgdTsqWcZ/HyeeXj6futKrliyzsDckq1V61UQ2SimyBbaxEX/uQJnPbiqZQzzo1coHTqdy2ibzpEXSeKFIccMvnsPNe44BAL5w2wv4yM1PGl5j5+kFmA1sPJHVPLjJbN7QtdFM1O8xnJKmcgX0xwJwuwg8CsHWAZaI2R7yoj/u1xNpbewNgLN28YvBvIJeQsjrASiU0vMA9BNC1tV2WM657szlGE9kteDmXsF8zcttPamqfaebAqM1XWEcn0w6OiYZmk7jv+48AK/iwmu29+PKzT1wuwjOWtVueF0s6MFnr9uGWNCjHQdw5YMHh2Nz7Hgn4vcg4nNrCWbcz3vt9n7MpPNaNqy4eKRzBcPFyP1/c5m8ZX1cXtP0t88OYTyRxUDcr5nzX326fkTBg6sXh+fQEfLB71Hw4cvX4W1nr9A6u9z23DC2DsSwrjuMzrAXj6hJhE+8NIk1XSG0hbzoCpcqvT989BhcBNrxH2dNVxgD8UDZUiki//SrvfjQ95/Ax37yNAbiAQS9Cn725AkEvQpWd4UNr40FPFjTFTKoF3wu3nfRagDAz54ozZwW4cEHtzf43ApO64viiaNTZf6VEUopHjg4pvlt5wQPnsj25XFs6o8ipj6ceYLmum7j7zXYaV3Wis/56s4wppKsEDm/3vj/K9X8BNhRa9TvRsCrYOdgO+766CW4dKNemP3vrtmIa7f3Y9dgO7xuF5a3B3FoLIGXJpJQXERb6KMBNzwKsfSzcRJVKL2HhUQhAFqVhw4LGwUPBo5PpjAyy0qs8YfLyo4gjownbB+8cYuGCNVSKFLLOr0i/EFuVmMHO0MLCHp1OwNXmewI+dzaeiEmO527pgODnSEt+Ddnlmv2hhKl14WgV4HbRbSvldTpdViyTJyTi9Z3YSAe0GwGKUGNNcM3jGIFGq4u+z3MfiG2vAXUoJe3Ic4brROv2NKHzrAP153JutlZ1eAFdLvRqs4QLlrfhWu29iHoUbTNF2/eYcZK6dWCXq+en9Ae8lra5PjPF5XesN9t6ek1WytEeHcx0eNdpMaSd+IG0e8x+mnTuSIiPjfWdoexsTeCT7xqE546Po0HhdKdnMkkq+hip/RmC0XDRsuqZBnAfN8ZB89tTW1Xf65mb1DK2xvmHAS9vLEJ70po3tjEAh6EvIpN0JtFLODR7qPjkyntGWFWhiml+L+/fA43PXAEP1efWfcdGCuZX6uyaRxW2SSjrS3JbKHkeheJBjwGO0Ja9Zl3R3xY3xOB1+3Cey5YhfdcsMqQgGiXyAa0eNALYDeAm9U/3wHgAvGbhJD3EUL2EEL2jI7O35jthHPXMO8Vfxjet38MA3G2I+Hltp4+PoW+mF9ThzhrukIoUlQsE3RgZA67/+1O3PXiKN6/ew2ifg/+4ZWb8L0/OUc75rNisCMEQoA37VwGj0K04IOXgQLUWn6q0ntolNUKfc3pAwD0ZLb3fmsP3vU/j2BkNo3XfuV+XPMf92qBr1jH0UpV42omVyf7YgG8bscAbv3LCzU1F2A3aK86P9z4/uHL1+Ps1R3oV1WjkdkMti+PgxCCnSvb8eiRCVBK8djRSa2ObGfEWJMvVyji5j3HcenGnhL1iRCCtd1hRx7ZsbkMhmfYsdjYXBbv370Gl2zsBqXA5v6o5XHy9uVthuxn7ue9YG0nXrmtD/999yE8UCbg3j/MXs/bXvJ/+9hLk467nj12dBJv+frDWsJlMmuvbgL6g3vvqRl0hr2GjHqAXVNWfcxH5zLwuV1Y3h7AZDKHXz9zCm/46gN46tiUpnges6gkYmZoOo1eGy8owDYqX7x+h/ZQXtUZwuHRBI6OJ9Ef9xuLkod8mkfcitlyQW/Ii2khOY8HFrwGdrfpWhX9iIlMQTuyfPzoFKZTOU2FXNEexGw6jyKFTdBrr/Te8uQJXPGFux10FitvbwD042bzUf1gR1BTY5xCKUUim0eP8LmV+wwBlqAjHkmKYwLsg3896C319BLCylCJ9X/FOr2OE9mEIEdxEbx513Lcd2AMR8YS2sPXCr5hFJXebIH9TI/CWgCXeHrdxuYU4hxsXRbDnn+4HNuWM7HETv0/PJZAxO82lvgSylnxkm5mwj43on63IcjhgZd4XfAqAGYSFkpvpETpZSWkym3C+HzyzWJa83jrYxDvlf54wFi9QQ2evv3us3Hz+8/FW89egc6wD9+4r7SikF2NXvZ7qOMwJclZ2xucJbKJ6m0qV7Cs08vnz+jpZX8uZ2+ICCXirII9Qohaq9fa3hAPerQTqKOCkGEuJ/qH50fw7QePIuhVtJ91ciqNsbmM4TSYb/CsNjhtIS+ePzWr3euJDFN6bYNev9sgrmVybPNx3ZnLcP1ZKwAAbzhzGT54yVpmS8noGybz58VjnXLPgsVkvkFvCACXyWYAGHr0UUpvpJTupJTu7OrqWsj4KhILeLBtWRz3HxxHrlDEQ4fGsXtDF9b1RLSg96ljUyXH3wB7gAOo6Ov97bOnkM4V8bsPX4iPXLEeALtpzSqvmd6YH7d88Hz88+u2YnN/DI8fnUQ6x9oP80WkL+7XjrcOjyWwrC2ATf1RRP1u3Ld/DCemUvjDvhHc+cIodn/uLhwYmcOp6RQ+/evnAbCgl3sBRyyDXmOA1Bf3w6O4tCoTIrxfeIfp2FdUjbgvd9eqdhybYL7myWROC3q7wqzOKX/A/X7vMMbmMnjL2cst56gv5teO1MuxV/0sv/Cm0/HD952Dt561Aq/Ywvqhbx2IW/6b7SviGE9kNZXkwOgcIn43uiI+fPYN27CqM4Q///4TmE7mtC4zPGOVUopfPnUSuwbbDA+VSzZ2o1CkjtVpXuLsy3fsx4hqrwiWWUh5cFYoUqzrjpR8f7AjhJPT6ZLTiTE1Izoe9GI6mcWLalWS3z43pCXBOKkKMDyTRk+0fMAksqozhMNjzN6wst1Yz9K8ARITkrL5IrL5Yhml1wOqtlSeTuY0xfiRwyzo5Z5eHpyJm5BENo8zVrTBoxA8oW5QuKKyQhij+Tpn76sGThYBzv8+dBT7R+YsW4uLsDq9DoNerznorb5sWSZfBKXsIczn04m9QfScuojR52gX/Js7sk2rahBXrsWgl9k8qgl6rWvw8hOix1+a1LymVvAObmLJuWxeL1F1zZZeXLjOmINhrNNrfZRuV9yfc3gsgdWdIYPKZ/Z72imt/fGAwd6QNim9AKuecMJiw8oDupBob/Cbgt4yR9gcr5up8boybWwSAhjvlYF4oKR6g9+joDfmR9TPvORXbOrGEy9NllgcygW9/HcWg0+7z8RpIlsyq1cdSOUKgr2htFa2GGzr9gb76g2aQs6DXot5XtkRxEOHJnCnyVo2lcwiHtSVXjF51bzB4adcr90xgJPTaTWvIY1cgRrWvWyB/a5WlU06VBGBk8wWkM7bn5pE/B7txKBQZPYNv1vBR67cgLefs9LwWtGLbTUPbUEvXDYtwhvBfIPeOQB8VQ0v4OfUhPPXduDJY1P45VMnkcgWcMHaTmzqi2LvyRlMJbM4Mp7UqhGIcK/moQqJI/cdGMOmvijWWgQhldi2LA6P4sKZK9vw1PEpLVGoU73p+2IB7SF6eCyBVZ1hKC6CV27rx63PDuGnj7HuZX+2ew0KRYrPvmEb3nfRGvzg0WP47bOnMJ3K4Qw14LRTenesiGu70gGbMkYAtCDLrICJD1Ce4HbWIAv4P/qjpwHoNVA7I8bj5l89fQo9UR8uXt9t+Z69MT/G5jLI5ov41gNHcP5n7sD5n7mjJKjkG5itAzGWWe0iuGRjF85d3VFim+Dwwuu8FvCBkTms7Q6DEGbU/9frtmEikcXv9g7hZ0+cwLGJFH6izvejRyZxaCyBN+00Bus7lscR9btLFjE7XhieRdCrIFeg+NzvXkAyW0C4zELqUVxa4MI3ISJcdTafToyqiVnxAKs+wNXC7z/yEqaSObiIdUtsM0MzaU3xd8LqzhBSuQL2nprR2ghzOkI+LVh9YWgWZ37qdu2zqOSZaxOURu6Z9Aplinj1hrjJRwqwBb0t5GUbzZcmVU+vbm/glFN6zQrn8Exa64ZXSTHPF6nhoWqFlaeXj49SZ58VR5tLr1v7PSvZG4Jetx7kWAQW+mbCOA9cFbXy9AL8WNSs9BL135bPUeAPTvNGoCPkU8eS08p5WcF9u2Iip1hK6p9eu0VTqTgexYUiZQ92u6N03TZhH/SaGxgEfeUDAU5/PKA1DQKEObBQes0BJK9SIlaCCZsS2coFNqXjNSq94hjCPr2TYH8sYLI3FEq6/23oiWAymStJXuKbYKt7L2jhrbWbO79HcVynlwfsqWxBb04hbEoDavCaFt531kkim5C4aTfOv7tmI3qjfrzrpkdx23N6ct90yujp5ad3iosY6ukD7DTFRZjVLZsvYu/JGXCBd9RwqmrdFAdASav76VQOlFp3NgSYPY3fx5m89X3J4R3tikVqOQ8uF0F7qHlq9c43WH0MuqXhdABHajKaeXL+2k4UihQf+8nTWN8TxqWndWNzfxRjcxmtVuLpQt1ZTsjnRl/Mrx17W5HM5vH40akShaBazlzZhky+qNXh4zd9f8yP8UQW6VwBR1TFAACuO3MAqVwB/3nnAWzoieBvr96IZ264Cm84cxk+fPk6DMQDWpegM8sEvYdG57C+O6KNv9yxJw+yzDdIwKugXe1Vz4Pmzf1R/OnFqxH2ubFlIKqp5uYEpn1DMzh9Wdz2uLc36gelrOHAb545hXyxiEQ2j289cMTwuudOstqwcaGaQdDrxvffdw52Dlor7qf1RtER8moNFA6MJLQSMQALYJe1BXDrM6e0bOPfPsfq0/7w0WMI+9x45bY+w890K6z5wp0vjGLf0EzFTPt9Q7PYOhDDm3Ytwy+eOomJRNYykU2EBy5mPy+gb9TMheBHNaXXg2S2gBeHZ0GIrtSdv7YTxyetC6Vz8oUiRmczFY/GjeNhY8wVKFa2G4PezrBub+B95l9QlXQtO9pvPRe60pjVrA0XqdewV3Fp3w96WX1jsWUuqwqh4IwVbXj6+DRm0nmDvUEcnxlzMhbn1mdOgU8dV8wnE1n8y63P48ePGdtq5wtFyzbEIjyAMD90eNWLarrqaWXwvIr2EK2k9IZ9iqGblDnY45sJ0R8L6EeoAY/RvytWPZhWS74xnyMBIcSgqALsJOU3z5wyqHUz6RzcLlKyEYgKyYXsSLa8p9dgb6jgaRVVaDsV2edWEPa5LZulpHMFnJhKleQUhLwmpdc26PWXTWQDWGevdK603msyY630zgpK71w6X9aCJ46XH+nzYFKcZ94IJuRVEA96ShLZzNfxetU69+KQ8dnKT/W6rZReD/s9jE0iqrM3/POv9+IHqv87my8iV6DapimVK+jNKUSl11PanMJpIht/bc6iVBcArO2O4BcfOh/9MT9+8ChLQqOUskS2AFPFvW6XpvSu6w6XNIKaVUs7LlNLoIkNuUTLQDZftD1hMj/T+bXkJJFNs7vYvJbnqKRyBc3bbKaziVoRzzfo/TmAtxNCvgDgTQB+XbMRzYMzVrTB53aBUuALb9oOn1vBZjVZ619+w2wAWy3sDQCzONzxwghuvOegZUmnRw5PIFsoav2p5wsPTP/3IVZejR/v8GSGJ49NYVYtI8Z/p1WdIWTzRVy1hSmZXuFB+cFL1uqd3dSgcsTUoGIqmcXYXBZrukP44CVr8Y+v2mRbpBwA1tvYGwDgtD4WOPMjPJeL4OPXnIbf/dVF+NWHLtSOVPTyJGlk80UcGU9q1SKs4AHW8EwaR8eTuHBdF167fQB3vTBq8BTtPTmjfaZOcbkILljXiXv3j+HkVApjcxlDNQRCCF6xtQ/37B/DvqFZbO6P4thECr97bgi/eeYUXn16v2WAesmGbozNZXD1f9yLd9/0qO37F4sULw7NYmNvBJedxoqQHx5LlFUPAP3hbXWyoNdytQt62Wd3YHQOV6idxiI+Ny7Z0I1UrsBq6f7rHbjFov3p2FwWRVrZDyqyqktXuFZ2mINeL8bUouSPHWULNVe1xM50VmhKbyKHw2MJVuJuIzst6Iro3Zy4j1Q8hucVMs5YGUdGbS/K68qyxhlebXxmeKMQs6r3m2eHtHJUL00kcWh0Drv/7S587e5D+J/7jd7FfMG6OYWI3kjFeD/GtAQy59Uj9KDXrXkE7Wr0coJCIpvV8btm8zAF/+IRqt+jGDy9fPzTqZxWEYEHlR6FGOrcPnx4An/23cfxh+f1ExOuyJurHCgugqjfzZTerH3yDeuy5jJcC1pGu9v689BV6KKt0guwe9IquZHfh2al1+zptQt6+2IBTCVzeucwC3uDVgXApP5rSq/w2ojPjWy+qKlz5coCGscrKr2lTUIAdr+0h73weRTVUsOa0qTzpRuRDeqab27+dHIqhXjQYxlMBk32Bp54ZmlvcJfaG45NJPH1ew/j+2pwyX8Of54lswXtelAMnl4etOnXZyKTN/jRreDzOpfJI6smbVrhcyt49fZ+3PPiKCYSWSRUxZmv81G/RwsItwzESqo3zKglF/npDc8NAsxKr/11xueAb8Yn1H/nK5PINpfJo6iWNgPsVWFRobdL2uyK+LB/ZM62LfNiMq+gl1I6A5bM9hCASyilC+vNukD8HgV/cdk6fOq1W7BFraW6bVkc56/twKb+KD529UbNO2PmY1dvxPruCD79m31ahrDI/QfG4FVc2GWjJjqlJ+rHW85egUNjLFmNP5R42ZqfPs7UIh4cE0K0rOFrtpQe31935jJtMRzsDKEz7C1Rermfd01XGJv7Y3j3BavKjnFjbxTre8LYsbyt5HvfeMcu/Mvrt1b8PbVMzdksDo8lmDfV4piewxWpQ6MJDM2ksbI9iNds70e2UMTvVPU1kWGVLMq1hLTjgrWdGJvL4GM/eRqKiwW5Itds6dV2/599wza4CPBn330cXrcL7794teXPvHpLL9553iAuXNeJI+MJ22LiJ6ZSSGQL2NAbxdmr2rXAwhzomOGL4XqLeYv6PegIeQ0Kc75QxEQyi66wT/u3lAIXrOvEjhVxnL26XVM4f/zYMRybSOHzt71YssnjKkw19oa+qF9TC1aYPb1hHytKns5rJdj4osePYCsGvaq9YUV7EJtUHzr383JiwpF6sUiRzLEKGWKJPB5MsnEG4VGI4WvG9/YYgr1UtoBHj0zgmi196Iv7cWwyhdv2DmM6lcN5azpKEk/yxWLF6g2avcF0LfAEMaeJkoDxmJv/TpU2LqLn1CrYi/jdIASYLklk049QxeY+PEGMB73c/8pboIqdzwDg3v3sxEtUZXk9ZSviQS+mktmyGecAsziIKrnWDc3m8+CfQy5fLOt/bQ95LT29h0ftg17R3mAnNui1XNk1lLaweAy0WZe+Slqokbr6yH7OTDqvWVHKIdpdrBLZAPZ82NAT1QLcjKqkFoq0JEDuCPvQGfbixSFz0JvWEqNLx2C0N/DPzmoj4rOo08vLee07NYN8oajdF/z0MZ3VlV5xU+pzu0CIsauhk81CuEIim8i1pw8gX2SnG/z65HYcviH3Ki6s6w5jNp3HrLDpnUmznAQ+b3vEoHfWGPTa2xvYHPDSpBPqxtBOvY363aCU2TxSFYLegJAIyDZ4pa+7dvsATk6lsPtzd2kCSKOofDfYQCmdhF7BoeF88JK1hr8HvAq++95zKv67rctiuPn95+KCz96BBw6O4+3nDgJgtoC//fHTeOLYFM5d3WHrZ6mGT79uK/7q8vU4MZXSkoW40vvrp0+hLejRHuwA8CcXrsY5q9stk86YR20zbt87grDPje6IH6OzGUwnc7ht7xD2j8xpF+maLvugUyTkc+O2v7rY8ntOf3+xEDVPprJKyOLwhzP3eq7sDGHH8jiWtwfwi6dO4o07l2Pf0IxapcFarS8H7xB27/4xXLu931BgG2Ae5YF4AJ1hL7YMxHDO6g48cngC//22M7Was2ZCPjdueM1m/PTx47h3/xiOTaQMCvJMOoffPjukBTAbeiMIet3YtaoN9x8YL3tkBrCArz3k1Y66zaztDhtqBQ/NpEFVhZYvpABLivrWu8+CixBNJbp5D9tcvTSRxG+eHcJrhLJ13G9eTSKby0Uw2BHCC8OzJZ5e3tTiD88Pa0mW/Ci3UkmgeEg/0j40yjyTfI67I8bxxYX2s6lcAZSyn9sfD6A3yhIlxQB3XXcE44lsiaJo+HlC4DSZzIJSFnysaA/i2EQSRUoxEA/gvDUdeODguOGIl3l6HdobTA8IHvRV072IK1pBj4LuiB99MX/ZEx2ABRjpXFH1spZ6el0utikwH+mLR6iXbezBqZk0rt+1XPts+AZEP8Zmn5XHZG+4Ty0tmRCO4mfSee2eMRMPejSl1645BX/dlCGRzb6ME6AnNOUKlPlfbX52m+ma4Bwasw56wz7FWSKbGsicmmZriJWnd5lNZ6+EYGvR3ldoD90e8mIuna/o7waY0ss/C6sqGgDwaVX04NazdK6gnfBZBUTruiOWSq95DeYETEGv2BbajN/jMpQsKxQpfvzYcQQ8ClK5Ag6OJsCnnB/tp3IFuNR7Xrw/CWGWmolkFn/+vcfx4cvXIZHJl01iA8xKLy3b9e60vgjWdYdxy5MntLyYmKD0AiwRk8cDp6bTmi1lJpVHNODWWsGPzrKOrul80RT02nt6eWWRzf1RtcZ9ZaWXvXfO9nrgcHtDImsf/F935jKcvaodl33+bty+dwRnrlyYiLgQ5h30LjXOWtWOu18YBaUUhBB87ncvYN/QLN5/8Wq8zZStuBC6Ij5D5ipXfBPZAnZv6DZkXnrdrrIXx6Ube7Qaql0RH05OpXDdfz+A/YJH2au4DO0D643foyDic6vtFFlW+Oou6+ARYDvKgEfBwzzobQ+CEIJXb+vH1+45hLG5DB46xL5nVYGjEr0xP9b3hPHi8Bz+9KI1Jd8nhOB/3rVLu1E//6bTMT6X1U4MysGtBkfHE4ag90u/349v3HdYU0x5abiL1nWxoLeCp/eDl6zVVH4rLt3YjX+5dR9OTKUwEA9oiv7qzpAhiFzVGdIWVH4NDM2kcf7aDgxNp/HVuw7i1dv0BiW8HWo19gYAWNMdwkQyW6KMXLqxG51hr+Y9P60vqilalToeRXxuuF2szu+R8QQuWNuJiN+DXYNtOGNl3PDaWMCjjV1XPdnPPWNlHL95Zshw0vOxazaWVVI7TKcm/Ag/FvBgeVsQv39+GFPJLLYOxLSTilPTaS3wyRcqJ7L5PC743K6STOuoX3/YOEX0H3748nX44/Mqr1eaIljmQdUW9FrYG3Ql57PXbSv5N7GAB0WqV8ThqnzAo5dIm0pm8bS6aROTrmbKKL08AE+r3crsMAe9dq1ZOTyAzxXKK71tQY+WUClyeCyBnqivZPMW9LoNzSniXuvfizef4MnMVp7eWIDVcy9RerN5uF3EMGb+uc6qrYhnMzmEfZVFj6DXjfG5pGEM5kCWWwJ4cJrOFcEvc6uAaENvROuMyq/zE5MpnLO6o+S1fAzs/c31o22qNwgnbPcdGMOp6TT++or1+PztL+LZE9NCNSJ2DSYFa4z5/gx6Ffx+7wiGZtI4c2WbWk+9gtLLg950Htl8oWzQSwjBlZt78NW7DmprC/fN82u+LejFgNDFjdsCZ9I5LFefi/1xPw6OJtAfD2A2nTesU8xiYZM7E/PD7SLYubINP37suObVt1d6dZsVV9TtAmRxs5Ip419f3h7E2u4w9p6asfz+YtHQqgvNxNmr2jGeyOLgaALHJpL43XNDeNs5K/HRqzZWTApZCH6Pou1EF+Ib7gr7sG9oFvtH5vCv123D7z9yMVZ2BLFtWaziUWut6Yr4cGo6hf3Ds1jZESp7HEkIQV/Mr9Ub5o0gXrO9H4Uixa3PnMKvnj6FM1bEq1IgRf70ojX4wO41tvaI9T0RLYDtiwUcBbziWMVyM7PpHH7w6DGEvAqGZtJY1hbQFseL1jPV2S55i3NaXxS7N1hXuwCAKzczu8vtajYwDzBWd4U1e4NXcRm6D4Z8bu06u3BdF67ftULrajcyk8Znbt2Hg6Nz8CgE7cFSr2s5/ubKDfjPP9pR8vWI34O/uXIDktmC6ivuwtBMmh09VkhkI4QgHvTitr1DSOeKmif/R+8/D+8zbV7iQpksPbmHXXPc4iAGU+0hb4kyJ9If02tnA3oJrKjfg+XtQYzNsYowW5fFtMYtYsZ1vmj/8OF4FZfl6YnXzZoozM/Tq6Aj7HNUZYYHGMlMwdbLyrzSJntDniWn2cEV9ReHedDL5kdsT/7AwXEtKVBMuqoU9I7NZdhRepnuYvGA15TIpnabq2Bv0Dy9tuXQvCVJfQC796yuJW5vKBYpMjn7gIgLIDwfw6pkGcBOGY6bqobwetTiiYVWO1bdTDhPZNOrTVRS9vjX07mCrsZarPHreyJIZAtasD6TzmE2Y688m+0N5Voo+92KZq0A9ATZd5w7CL/HhedOzmibLO7dZ3V61ZJlpms4oK7XAKswUa5xjjhe3nmvkr0BYMp3kertnnkNdn660R7yoleNNYaFMp6z6bwWhPI1vT8eYPeU6OnNW1sL2Bz48PuPXIw37mTtg7lVp1z1BoCpzBkbj7c+D4K9oUK1kNP6mNLcSKTSq3LWKrb7fPjwOA6NJuAixJFiUgv6Yn5MJLIlLY2rgR8lr+8J47ozlsHlIvj9Ry42JI8sFues6cCP9hxDPOjV+rqXozfmx6GxBCvWrQZtG3rYcdCN9x7CsYkU/lFtfTwf3lBGNV0IbUEPIn63wV/7w0ePYS6Tx4/efy4+9au9mocKADb2RvC567ZpCVnzZVVnCOu6w7ht7zDeef4qHBydQ9TPErT4kefy9kBJxYzlbQFMJLKazxlgvu+9J6fx33cfBCEs4LOq81iO1V3hkux1zht3LscPHj2G/rgfy9uDKBQpRmYzWg3IcBk1pS3owf4RVlv5qs3WZekAdkzIA1OzbeJ1OwYwmcxiY2/lQJAz0BZQTyrYsT/vShYLeAynJpv7o9rxtBgk5wu0YnOKgbYAlrdZH/NGA+6qPL1iIptT+NHtXCbPkk9sujgNm2po5wpFeMo81HjQemBkFi6iH6t2R3ya3em+A2MI+9zwexSTvSFn67OOB3U1v6yn10bptRuzWL0hY1F6i9Me9OreTeFnHR5L4OotfSWv52UJkzyj3eb9/R7mw+b2H25VMf+OKzuCWrMcjlWjG/HInVLKvKlOPL1ih76cvcIK6MFPOl+AQuztDRt62ZrwwtAslrcHNT9/v03ZTHOdXv7ssuzIJgTeIR+7XxQXQTTgxml9UTx7clp7nvI8E9EaY7Yficr62GwWiWxeyyuwgxCCsJdVy8gWiohXKA3HTzx5s6ASpTfk1RNZU+bNIPsM+XrTF/NDcRFD7fVcofyGlAs7Qa+iBb3lqjcA7J7kG3g7i2NQsDekbaptcE7ri+Anjx9X28Bb2/fqjVR6VQY7guiK+PCdB4/iuw8fxSu29tVV4TW8d2cIKzuChnJK1cJLwHzwkrVa0MK7EC02f37JWhAQjM5myiaxcfhxuljyihCC15zej2MTKRCCktJhzQAhBKvUtrGFIsWP9hzDV+48gLNWtWPXYDt++mfn43PCETAhBG/cubwmN/uVm3vw8OEJraTX6i5WfziklvCyUp8GO0NoD3mxqU8vMXdwdA4vDM/C7SKaL7iWKC6Cm//0XHzp+h2alefkVEpTYcr55vhD5zWn95cNdGIBD2YzeeQLxZKC/R1hHz561caqTjv4Q5l7nLnVIBpwG/yIWwdi2nyJSm+5hBLOX12+Hj96/7mW34v6PVV5epMW9Vorwecnmc0jUyhaKnUdIa+hvTPAgshyihZ/OL84PIfOsE+b9+6IDyMzLLB77sQ0Tl8eQ1vQo21SKKXMu2ijSsYDXi2ALR/0ejGVzGml+fTWrHbVG3giGy2r9MZDvGmJ4PVOZDGZzGllJkV0JZ0Fyr4yc9YT9WkBfTJXgEchJdfP1oEYDo0lTE1YCiVJsWJyFU80c5LIJnbo00uW2VfJAJi9wa6hCADtXuHVCCoFvbwdsK702ich6mPglhm98seW/hj2npzRrq0OQenVE9mMPzMgbBjH5jJVVL1gdZFz+fL3BaD7vrnSy4Ndfs23B70IeRW4iG6pKhYp5rJllN4Se4ODmsxe5l8G7D9jHnzPpvNCYqP1z+bX4MgMq9hU7vnGc5YaqfbKoFeFEIKzBtuxb2gWG3qj+IdXnbZo733Dqzfjf99ztm1ijRNesbUPN7x6E161rb/yi+tMfzyAt57DisCXK1fG4d5Xc+LYq9Ukq7MG2+dtbag3KztCODqexFfuPICP/vhprGgP4lOv3QKABXwL+UzLceUmVnXijn0jODg6pwWxhBCcs7pDs1KI/N01G/G/7zkbLhfBQDwAn9uFgyNzrHHEyjZ8+nVb8ScXWlesWAhetwtuxaWXXppKYS6Tg9/jKhuMcquGuUFIyeu0Ml95zdNbKQmlHPz4lR/L8kAj6vdoG9P+mB8dYR/8HgUdIa9B6S04SGRzK67yfe/nY28oEwyaCQmKYCZnfSTZEfZhIpE11HbO5Ms/WPnD8thkUjt9Aljb6NlMHqlsASem0ljeFkTI59YU/3SuiGyhqAXNZvi1AFgHWOLrsoWi5kutXKeXqL9XwbZdMADN8iMm9h22KVcGmJKcyvgcAZbsNzyjK71W1wVvrvSskMCazJQqvbyKBqsAkDd8rRxBtcFAQShRZafsceU1pXb1AqwDovagF4TotWR5uUK7BkluhXWGK7E3WMyHpvSqn+90KqetA1sGopjL5PH8KXaywDfPYsmyUqWX/bxlbQGMJbKOEtkAtslIZPNl1XxOxO9Bd8SH2XQeAY+ifc4xQenljZP4ZzebyWvdFgF9beqL+dEV9mEimdUsG7m8fSKbSMjr1koy2pXoE3ML7ErYcfgGj+eWlBNOTmuCoFfaGwQ+sHsNNvRG8L6LVpdVE2qNVUvGaukI+/DO88uXJFtM/uLSdcgVirjYIvgywxXAQVP2/2BnCB+9akPFds+NZLAjiF8/fRLffvAoLl7fhZvetatuga7I1oEYeqN+/PTxExieyRiSBb/znrMt/01fLKCdXrhcBKu7wjgwOocXh+fw+jMG8JazV1j+u1rBM5NPTqUxlykg7CvvNTxrVTtyhWLFBMZ4UFfhnBSVr8SAME5AV10ifjcUF0HQq2Cz4PvuMzUYyBWpoeNTtbDj7sqtuTmJbF7bWDiFP9CTmYJtUNYZ9iJbKGI2oytNlewN/AFOqd41D9BPoo5NJjE2l1E7kaU0NU5MFrRC9PqWL1mmV/0Iet2q6m6/+eTBMN/Y2AU6vMWxWLZMK1dmkairHflmytsbAGZNO3yI/ax0rlS9BYBtaqv1J49NabkflZTeWe26deDp9ekNBio1I9BU1nwB7qK9vcGtuNAe9GJUPS04OZWCRyFaCTErAl5FKx1WvnqDUekVy93xDcJ9B1hZvLCPJUunBaXXbD+KBTwYiAdw1mA7Hj48gUSm4GgN4Ru3bIXNIGdVZwgjsxnDJo5v9NqDut2B3w/6KZNq+1NtWtwvTSm7JrujfrZptEmYFAn6FK0znV0gy6+jmXROC4xt6/Sq1w6vZFIu6G0LedEb9WPvSRn0NgVbBmKOk5gk5WkLefGp11au6wtAM++vsCgRZi5F12wMdoRQpOxI7B3nrlyUgBdgQeuVm3vw7QdZsxOnZelE1nSFcOe+EbWWcPUttqsl7GNtck9Np7SuaeV474Wr8V4HyrPYRY0nslWqhVyOXsGGwX9u2OfWgspPvXaLYb77YgG8JCQz5gtFQ8enaon63dg/UoXSmyloiXtOCQnVG+y6XvFj4fG5rCHoLXdULwat3cLpDP/zky9NAWAbi+d9bu1YX1TTrYgLPzfgLXc6oNd37o8HKlpNeADPg1m7jRhPAhU3I3yjY6VcmqtjlPM59kT9GJlNg1LK2ixbBBexoAerOkN4Sj0aB5g1pcdUvi/gYcfjc+l8xQopIqIdI51jDUjsNlE8UMrkCsi7rEvvcTrDevvZE5Mp9FXIGQgKCXV69QaLOr3u0qCXf0bruyOIBz149gQLrII+BQEva76Rs6jTCwAfv+Y0pHIF/OyJExibyyBbKDqat4jahKRc1QKR1V1hPHx4wnCf6CXL2Pgjgr2JB7/8NduWxfHQxy9Db8yvtSofmc2gO+qv6OnliN5/u0BWcRFEfG7MpPRESFt7g/ozDqvVTSrVeT+tL6Kp8I1A2hskDef05TGcvjyOs5tY0bVjsFM/7i5XcaEeXLlJT+5aU6YsnB2ru8Ja4tsGBzaUWtAfD6ie3tKj2fkS09rP5ip2enOCz61oJQABllQiPqRef8YyTU0C2GfPfYvFIkWRlipJ1RANVOvpLVSVxAbont4Er95gEbTw9q3jQoZ4Nl+07W4GsHnnv7vYRIT/+YljLIlnoC2g+SEBXdGyT2TTk4rsAiz2OnUDpNoQKlkLeEDMu63ZKb1r1Mood+7TO8hNJHIIeRXLwEHbVDiyN/iQK1BMJnOGslpmti2L4enjor2hoJXm4/Dj8blMXptbJ55ePUgvqK2e7edYTyIrVqz00BnR28+enEpVrBkc8CpI5szVG8rYG3K6vYFfOy4X0ZpJKS7WAjvgUZDKFlHQ7A3G8Q52hnBaXxSdYa/abc7ZaRGf61wZa4wIX6fFJDl+zfL7LeJ3ayo9tzmIth++KRdr4gPOcgkAGDbI5cbMFedKHdm4LYUH4d3R8ifXp/VFcXB0zrapU72RQa+k4XRH/Ljlg+fbFi1vZlZ3huFRCN56zsoFBTrz4ezV7Yj43XARlDSGcIIYKK9fBKUXAAbiTKGYSztLFHECVwGnkznN3lBtEGiGH78DTG0pFzj0qTUz5zJ5rQRXpZJl5Yj6PZhN51As0sovBlP8qlW2eXDHVCo7Ty97MI8JyWyVHqyEEK0Ek+jD500qnhCU3rDPrc2XpmiVqd7A8Zf5XfnruPc2W6ZgP6B/Tvz1dp+zR3Hh6s29uH3vsBYETCQyWsc5M3x+J5M55C06lonweRqeSdvaGwDWbn5oJm2oSW2l8Ef8LEGQVx1xVL3Bq18P6bx9FQvAaC2o1K2rM+zTkiFZ0Fs+OTzoVbROc5my1Rt0tRnQE9k4XEDhJd0CXmZvyNsoveJ4OU7tDRMJFhg6U3rZmitez+es7sANr96Es1ezMbP737gZtDoB4Zah0Rke9Drz9IobpXKbm4jfjZlUTpvjcgFy0KeAUpb8WqkxzjvPH8QDH7+04uvqhQx6JZIF0Bby4vcfuRjvv7i08UW98SguvGpbP7YMxOa1gPAj+v6Y3/ZYudZs6I3gwMgcTk6nahb0ivaGRJZlvzt5AJVjIO432BvsFEhA96S/7RsP4/T/exuAhXmKeYOHRNaZ2pvIlip+leCbgnLH7zwAGE+IGeKVH6x8rrqFXIW2oAceheDFYVbKrDfmR8TPjoYppYK9wSaRTfT0lrnW+XXMlTJ25Gs/Xv49XpWhnM/8ldv6kMgWcPeLzCs6kczZ1rTmnz8v01Yu2OMq+MhshpXVsgt6lzPrHbc4JDPWCn/IpxjsDZEK3nlxvMlsAelsaYc+ETHo1QIiO6VXtTfkCkUMzaRtk9g4QY/evtmRpzfPaiHPpHOGa4Q3wOAnGkHV3qAFvTYChRj0VrJfASwwHJtjjZicVF9a3cnWXDHo9SguvPP8Vdp9FfW7dU8vV3ot1meu9PJNkFNfsWOl168qvfki/B5XWesetzg4STjvjvhLumouJtLTK5EsELt2xYvBJ6/drCVnVAtXHRbDz8u5dGMPvnLnQRyfTOHMlW01+ZkxIXnJKqN9PvTHArhz36haSitX9hSCP8ifPzWDD16yBpv6YrjstPlbXbTC8A4bC8ykco4y9EUUF2u9Ope29/TyI1ixbFmlzlOA/nmID0BCWALTyek0+mJ+eBQXwj43ipQlT3E7h5NEtnIt0blSy5Uyx/YGtfFEuY3Yuas70B7y4ldPn8JVm3sxkcjYJmXxa5BnqZc7ieEBwPBMGqlcwRAQifCA6dhkCpRSJGwUft3eUF69FqlO6dUrJ5Sr0wuwIDKZLeDF4VkUaeW1MuBVNKtJKmdvbwhogXcRs2lW4UC8Rk7riyLid2u/l19tT6yVLLPx3BuUXgenRW/etRxRvxtXbenF5v7K+UDL2gKI+t1avV0rogELpdeiqonfo6At6NGaauQcVJAA9A2vVyntCGkchxsnp9KGFut28Huyr8YlL+uBDHolkhbGo7gw30IjQa8br9zah4s3VK6wUSu2L4+z+q+JbM08vW7FhYjPjalU1lH7UCf0xwNI5QqYSuZYcfgywef25XF89KoNuGpzj6NuaJXg7zWdzFVUxgBgdDZjWSu2EiGfUKTe4iLyul2I+t0GT2+lOr2AHnyYvX3dUT9OTutqn1Y2LZ0vyVI34/co8HtcSOfKtyEOed0gxKj0lrOaaIlsmtJrf+24FRcu29iN258fBsACZbuSjFz54kHvyjKbJq0r20zatmQZwNRBr9uF4Zk0xuayKFLryj9RtXvdbBX2BjGxsaKnV0gi04JeG2WYW2QeO8q83OYKPWaCXgUnpliwe2h0DiGvojU4MYxBKJs2beEHV1wEuzd0awp+wKNgKpm1LVnG6Yzo7+XkJOq0vqhWhssJbsWFWz98keXvxOGeXkqp/hnajKUnqpe7c57Ixj4rO3WeE/V7sC89y67JCieJ/PrpkUGvRCJpZr7y1jMW9f34w+gnjx+vWp0sR1RtRZyyKOM0H/qFmsIz6XxZe4NbcdW0yggP/JzU6qWUYlTN3q6WkM+NBw6OA7BPZOwM+zCWMHt6yz9YYwEPFBfREnM43O7A5zYilNeaTuUQ9Cplj2fjAS+GcumyKqTLxRK5+LFwxeoN3NPLqzdUCBBXdYUw9VgOyWwe44mMbfDC6jC7MDaXhd/jKluWUuzKlirj6eUt209Np7XKEVbK2kA8gCePTWEuk4ff43LcsABglom0TQUJjsvF7EPpXBGKi93TdtcEV8L3HFGD3gqbM1ayjAW9e0/N4LS+qKUaKdobeNAbN1lNxMZAQa+CU9NM6XUR2CqcvLaw00S2+VBpIxvxu1V7UwEzaZYsaVdJgwW9XOl1WKdX/b0qWeJYQq1ubygHv14qVW5oBqSnVyKRLCqXq0f/tXyoxNVWxImss/qaleAPpqPjScxl8rZNE+qBWBi+ElPJHLKFosE/65Sg142hmTQUF9GSaMx0hL0mpbfyEerG3gg290dLEju58jugtnIWGzjMpMur6YDug6x01ComAlUqJcVVa57IVqkhAT+WPjyWQDpX1MpMWcFPHFa0ByuWMuRd2exKlnF6o34MT6fLdjdb0R7EVDKH41OpirWwzWNlSm/l42y/24W0WtPX77b3e3ZqQe8Ewj53WYUT0L23xSLF86dmbVVUXW0uYirFNizmjalfaAAR8Chqcwpqa20A2GaF23oa0c0UMPrSZ4T6w1b0Rv0YmkkjpzZkKWf94eiWj/L3cV/Mj5l0HsMz6YrXA/+ZMuiVSCQSExeu78Ly9kBNvcTxoIeVLHPYSakS3O/8xEtMoSqn9NaamKb0Vk5kG1brxlYqE2QFT9Q5fVnM1jvcEfIZPL2VOrIBwJ9fug63fPD8kq9z7yrfUIQN9obKGwvWZrZ88g1gLPlUWenVS5Z5FVdF9YuXi3pOLa5fLojjQZOTBKeeqB9D02lWsqxM4NIb8+PUTKpsd7OVqoXg+ZMztomBZniDgaRWsqz8HPs9CjL5QsUAmdsFTk6nsbKjcvA/2BHCZDKHhw6NYy6Tx6Z+66DXp5UsE5Ve+3uUV28oFIsVq+x0qpaMWiXaVktE2/RW3gz2xPwYm8vgyFgChSJ1lF/CNziVAlk+908fn7K0P4nwRNpat7GvBzLolUgki0rY58a9f3sprtrcW/nFDokFPFpHtoWWKwNYwDIQD2CP6kVcrOoWgJ60Mu1A6R1R/XzzadPN5+kCtcOXFR1h5r/mVKqGwLEKbnpMSi8PCmdVe0OljUUs4IHfrVQMnFjQy+0N5T3IPOgtFKkj7yu3E/COUm021RsAMeitHIh0RXx46vg0svmibUUIgAUVw9MZnJxKwe9xWQZ6POny8HjC0e8EMMXb7SJaIlulIMfvUdQ6veX9v6LFpZK1AQAuO60HAPClO/YDADbZKL0+twuEsJJlU8nyNZ4BpkSyerrUtlwZh6vTtdg8zwc9GTOH2XT5zWBv1A9KgYcOMZvSagf12vkGp9Lmkc8989GXfy33sLdC0Cs9vRKJpOUZ7AjhtueGEfa7q0osKce6njDuPzAGwD7Bqh5whcmJvWFklgW987E38If6eWWDXh8mk1nkC0W4FRcLIudZDm778jYsbw9gs6og8Yd7QrU3VDoabQ95Hfm1I369jXM2XywbDIleVCfKHt9cPHdyWhuTHbw01EoHNbSvO3MZFEJw4fouXF1mM9intpt99sQ0+uMByw0AV5YpdVa5AWCbFN4NLZMrVkxcYkmFBbhcpGxClNftQkz121dKYgNYm941XSE8dGgCLmJfWYYQAp/bhXS+aJnIZibq92jNNOyS2Dha0FuDzfN84GvNbJrdF+XKe/XG2Fi5N39NZ+XOnE6V3o6wT7NPOLU3zGfzvdjMa/UihPQQQu6t9WAkEolkPly7fQD5IsVUMleTRDaA9bfPFViJo8W0N7jVcl5OEtl4cDefupexgAcBj4IdK+K2r+kMe0Ep87wWihSForNkGSs29EZw799eqo1V9PQ6UXrfe+Fq/KuQnGSHUektn3hHiJ6E5cTD6fcoaA95tTaqZYPeKuwN563pxOfeeDpec3p/2U0FV9KePj5tmxAV8Xu0cVVzRB9SW+qmcuVLlgF6CbC0g8x+bhdwWtrxCrXT5OqucIXOcMyyMJPKwed2lX0t79o4kcjaJoVxBjtD6In6ypbzqid8ozKTzjHbT5mNCw8yHzw0js6wV/s9yxFw6OkFdItDpc94bU8EqzpDju00jaTq1YsQ0gbgWwAaV5xUIpFIBDb0RrBlgC3QtUpAWdutqyaLmcgGsIDUSSvikZkMIn63owQWMx+4eC2++c5dZX2sWiviREZrdlCrTYVmb1BLllVS09d2h7Xj73KIQW+2UIS3wgObB/FOq4n0Rv3aXJQLennAOZ9uibbvrSbSpXKFsjVRucXBaSIbwD4P5ul1ksjGAs5KNX0BXTld5bCs3hWbWKKrnbXBPAZzNzYruD1pIpGtqPR+4OI1uOWDFzgaaz3Qg948ZtOVE9kAltC62oHKC+hKr5OGRvxUptJn/PZzVuLOv9ld0XrUDMxny14A8GYAMzUei0Qikcyb1+9YBqB2x5LrhKB3MZVegD34HHl6Z9PzsjYALBg7d01H2dfwOqvjc1mMqVUcOm0aMlSLz+2CRyGYSecwmymvaFVDRG3jTClVu1SVfxDzoNep/5UHm4qLlPV6sxa4rCFBrRAtIOW6vHF12am9AWB2jJl0Tg16y4cGPrVmciVPL6BfL05sHgCzwVy4rhOv2Fre88/rNk+ncmWT2AD9/mVKb/nrIeBVGupN5dfU6Ewa06lc2Y1VW9CrXd9rup1tKrin15HS28eD3sb4m+tBxTuCEPI1ABuEL91BKf1kuYieEPI+AO8DgBUrVix0jBKJRFKR12zvxxduf1FLlFoo64TatYuZyAYwBXFUKBVmx8hMpq4tPXnAMjqb0RSyWgW9hLCauk+8NAVKgRU16mwY8buRK1Bk8kVHiXc86HV6QsADoragp+wR+DmrO5Cs0NK3WroiPigugkKRVgh6jbWQnRD0uvHI4QkUKSp2F/N7FIzOZqC4SMUN4fL2INpDXtvudWYUF8F33nN2xddp9oa0A6VXPakZT2TLBpHNgN+jwKu48OiRSRQpsLHXXvF2uQi6I36cmErVSemNaWNaKlS8Iyilf1rtD6WU3gjgRgDYuXPn/HqkSiQSSRV0hn148OOX1kzpDfvc6I/5MTKbqdmRvlM29UXx7YeOVmyjOzKbwRllPLkLhVdcGJlNa8Gh2LVqoYT9bq1b11mD1rWCq0Ur+ZTOOUq8412snPpfebBZKXh6w5nL8IYzlzn6mU5RXATdER9OCZ3trFipVoyoSun1Kcjki4j63bh0Y/k22qxkWREugrJ1hQHgg5eswVvOWlHzo2+fR1ET2fIYiJff+PGgeDqVK9sopFmIBtx4XC2XuNmmbBunN6YGvQ4qNwDVKb3L2wNY3RXCmm5nAXUrIEuWSSSSJUPEX159q5Z1PRFEA55F96ptXxFHNl/EviF7FxmlFMMz6Xl1Y3NK2OdG0KtgaDpTc3sDwFSnQpGiJ+rD8vbaKPRRv+4VzjqoK8xbETsNELnFoFy5snrCk5dq7enlJexefXp/Vc0pKrWzjfg9NfU1m8cwk8ohFij/WYgnNZU8vc1AxO/RNiCV7DH8elzT5Sww5eXFnCi9hBD84SMX4+3nrHT0s1sBGfRKJBKJDW89ewXeed7gor/v9uVxAMBTx6ZsXzOTziOTn183NqcQQlir09k0xuYycJHaBns80Nw52F6zjUVEDHorNKcABHuDwxMCHmxyv/Niw9+/nL1hU18Ua7vDWnKnE3gJu9efUVmdDngVzKbzaqvjxhx9+z2KWqc368DeIAS9FTy9zQC/hjf1RyveF8vaAwh4FMfecbfiQk/U59i33ArJadUw73NASunuGo5DIpFImo4rN/fiyho20XDKQDyAzrAXTxybwtvPtX7NqFqurN7HtT1RH0Zm0oj43GgP+Sp2tKoGbinYtbKtZj8zIrRxddI2udpENt3T25igd3N/FAdG5iqW6Pr9Ry6u6ueevaoDY3NZR3aZqzb34jsPHQWllctZ1Qu/x4V9Q7PI5ItY11Ne5fR7FHjdLmTzxbJtiJsFrkxv6ivvrQZYtYnXnN5fsRSbyG//8qKGtVluNM3/6UskEsnLDEIIti+P48kySu9CurFVQ0/Uj+EZZm/orLG6GVYf7rtW1cbPC+gq2dB0GpRW9pxyT6/TkmV9sQBcpP6bDTv+bPda/OYvL6z5z33tjgF8/R07HSl756/txIcuWQvAmTe0HnBfccir4NWn91d8PVeDW8PeoCu9lYgHvRUTD820hbzzbjLT6rw8Q32JRCJpcrYvj+P3z49gOpmzLDq/f2QOgLPmBwuhR+3K1Bby1jzQ6wh5EQt4ymaoVwtXep86PgUAWNVZfn6qrd4Q8Cr45jt3YctAdYFGrXC5CFxofOD2l5evBwBctWXxT0IAXWF+7Y4BR0mIUb+bVSFpIXtDpSQ2SfW8PEN9iUQiaXK2L2dH/g8dHrf8/qNHJtAf85f1dtaCnqgf2XwRh0bmaprEBgAfunQtfvT+c+timeAqeaUEn2rtDQCwe0N3zeei1VBcBB+5ckPVKmOt4ArzW892lmSlK73NH/Z0RXwIeBTHyWkS50ilVyKRSJqQXavasKwtgC/c9iIu29ht8OxRSvHokQmcvap8c4lawMuWzWbyNbc3dIR96Khx8MiD3n2nZuEilTui8eoN1bTslTSe12wfQFfE58gCAOjJbLXcYNWL9124Bq/aVr4ltWR+yBmVSCSSJsTnVvD3rzgNLwzP4vuPvGT43vHJFIZnMtg1WLsEMDtEz3Ar1DhVXKzpRb5IsaI9WLE0U7V1eiXNwZkr2/Dnl65z/Hqu9Fbq0NcMxIIenFahDbNkfsigVyKRSJqUq7f04pzV7fjSHQdQLOp9fh45PAGgtglgdoitb1vlSJ97Ip0cD8/H3iBpPXhFhFZQeiX1Qwa9EolE0qQQQnD9rhUYnc3g6RPT2tf3HJ1AxO/G+u5ImX9dG0R1t+WCXgedpLSgVyq9SxrN01tFaS/J0kN++hKJRNLEXLy+Cy4C3LFvBADz8z54cBw7V7bVtPucHX6PgrhaPaJ1gl423tWdlVuz6s0pGlNvVrI4RANsU9MKJcsk9UMGvRKJRNLEtIW82LGiDXeqQe99B8ZwZDyJa7b2LdoYuMWhM9KYhgzVUo3S63UTBDyKVACXOK1UvUFSP+SnL5FIJE3OpRu78cyJaYzMpPH1ew+jK+LDtdsrF+SvFd1RPwgB2hvUhaxauNLrxNO7rjuCbcsaU3ZLsnhwT69Uel/eyKBXIpFImpxLN3YDAD74vcdxz4uj+ONzV1asSlBLVrQH0Bv1t4wa2h/3oz/mR3uocpD+7gtW4Yd/atPrWbJk0D29Muh9OSOd+xKJRNLkbOyN4C8uXYsfP3Yc8aDHcUH+WvGRKzbgnecNLup7LoQPX7Ye77lgVaOHIWkioi3UhlhSP2TQK5FIJE0OIaz71V9dsR75ItWSrxaL9pDXkWraLAS8CgIyMU0iENOaU7TGaYWkPsigVyKRSFoEQkhLFNeXSJoN7umV98/LG7nlkUgkEolEsqSJ+N3wKAQ+jzwBeDkjlV6JRCKRSCRLGpeL4KZ3nYV1PZUrekiWLjLolUgkEolEsuQ5f21no4cgaTDS3iCRSCQSiUQiWfLIoFcikUgkEolEsuSRQa9EIpFIJBKJZMkjg16JRCKRSCQSyZKHUErr+waEzAJ4oa5vUn9iAKYbPYgF0sq/QyeAsUYPYoG08vy38tgBef00glYbrxWtfN0shflv5d+hla8dTivP/wZKacTqG4tRveEFSunORXifukEIuZFS+r5Gj2MhtPLvQAjZI6+hxtHKYwfk9dMIWm28VrTydbNE5r9lf4dWvnY4rT7/dt+T9gZn/LLRA6gBS+F3aGVaef5beexLhVb7DFptvEuNpTD/S+F3aGWW5Pwvhr2h5Xc8ksYiryHJQpDXj2Q+yOtGMl/ktdNYys3/Yii9Ny7Ce0iWNvIakiwEef1I5oO8biTzRV47jcV2/uuu9EokEolEIpFIJI1GenolEolEIpFIJEuemge9hJAbCCFvK/P9u2r9npLWhxASJoT8jBByPyHkW4QQy8oihJDthJDtizw8SQtRaQ2SSDiEkHZCyBwhxN/osUhaFxn3tA5S6ZU0Cx8CsJ9Sej4AH4A32bxuu/qfRCKRLJQrwNabixo9EIlEUn/qVaf3BkLIcUrpXYSQdwIApfSmOr2XZGlwNoBvqH++D8AuQshrACwDMAUWBH8CwOsAgBDydkrpZQ0Yp6RFIIT8BoAfwFFK6bsIITcA8AC4AKzw+tWU0qEGDlHSeK4G8BUAVxNCzgNbh4IARgFcTynNqyrdLQDeRSnd1rCRSpodGfe0AFLplTQLEQAJ9c9JAB8G8BSl9AIAPwGwhVL6cQCfAfAZGfBKKrAKLJi5BsAgIaRH/fpaSunFAL4H4NJGDU7SNJwL4FMA+Hpyr3p9DAO4Vv1aHwAqA16JpPWpSdBLCLmeELJb+FJB+HOgFu8hWfLMAAirfw4BuAnAI+rfbwLw6OIPSdIqWKxBeQDvBfBdAO3Q16Fvq/8fAeBdrPFJmg9CyDawdrE/BjAIYDmAx9RvP61+DWCtWL+0yMOTNDky7mlNaqX0BgGcr/55FdiDhfc9vrpG7yFZ2jwMYLf65wsBHAGwS/37/wcWwABACux6AyGELN7wJE2OeQ26FCyY+SPoJwgw/Vny8uYqAJ+mlO4GC2qvAnCW+r0dAA6of05SSouLPzxJkyPjnhakVkHvDwGcTwi5W/37LQA+Sgj5bwDjNXoPydLmywBWE0IeAAtsPw/gDNVPdwaA76ivux3A6wkh94MFxxIJULoG/ROAjwO4Q/37QENGJWlmroJ+fdwB4CGwXIK7AMSxRNuwSmqGjHtaENmcQiKRSCQve9REx7sopXc1eCgSiaROyKBXIpFIJBKJRLLkkdUbJBKJRCKRSCRLHhn0SiSSloUQEiOE3EoIuV3t6OclhPw/QsgDhJB/EF7XQwi51+LfbyGE3La4o5ZIJBJJI5BBr0QiaWXeCuALlNIrAAwBuB6AQik9D0A/IWQdIaQNwLfASuFpqNU/vgBZukwikUheFsigVyKRtCyU0v+ilN6u/rULwNsA3Kz+/Q6w7msFAG8GqwUt8i4Ady7GOCUSiUTSeGTQK5FIWh5CyLkA2gAcA3BC/fIMgB5K6QyldNr0+g6wAPnfFnWgEolEImkYMuiVSCQtDSGkHcB/Ang3gDno3ZDCsF/jPgPg45TSXP1HKJFIJJJmQAa9EomkZSGEeMHsDB+nlB4FayN7gfrt08E6+1lxMYDPqo0IthNCPlXnoUokEomkwcg6vRKJpGUhhHwAwKcBPKV+6X8AfATAHwBcA+Acbm0ghNyltpw1/wzLr0skEolkaSGDXolEsqRQqzVcAeAeSulQo8cjkUgkkuZABr0SiUQikUgkkiWP9PRKJBKJRCKRSJY8MuiVSCQSiUQikSx5ZNArkUgkEolEIlnyyKBXIpFIJBKJRLLkkUGvRCKRNBGEkEFCyO4qXv9OQsg7a/XzJBKJZKkig16JRCJpLgYB7G7inyeRSCQtibvRA5BIJJJWQe3g9iiAbZTSqwghQQDfBtAN4BlK6QcJITcAOBtAEMAogOsppXlCyH8C2A5gCsA7KKWT6s+7BcC7KKXbCCF/CeBdAOKqOvtGSumoxTg8YJ3o4gByAL5HCFEAfAdAP4BpANcB+DPzzwMwBuBGAOvV8b2ZUlqo1RxJJBJJsyKVXolEInHOOQAepJRepf79fQCepZReBKCPELJN/fq9lNKLAQwDuJYQ8ioAfkrphQB+DOBj6uv6AFBK6TawP3wRwIcB3EQp3W0V8Kq8HsBRSuklAI6qX+sA8GsAlwOYAXCGzc+7FoBHHd9LAF65sCmRSCSS1kAqvRKJROKcZymlPxX+vgHAeaqKGgcwoH79MfX/T4PZCxQAD6tfexgsaAWYIvuleYxjlfqzAWCP+v8cgFeBKbzdAAI2/3YDgHNVlTkM4Pl5vL9EIpG0HFLplUgkEufMmf7+AoD/oJTuBvAPYMopAJyl/n8HgAMAngNTiaH+/zn1z0lKadH0M1Ng1ggQQojNOI4C2CS8B8AC6WfV/58o8/NeAPADdcwfBrDX5j0kEolkSSGDXolEIpk/XwdwDSHkHgDvB3BM/fouVUmNA/glpfTXAFKEkHsBvAHA58r8zCcAbFBf+2ab1/wUwHr1PdarX7tfff19ANqhq87mn/cLAP2EkLsBfAq6PUIikUiWNIRS2ugxSCQSyZJBTWS7i1J6V4OHIpFIJBIBGfRKJBJJE0MI+QGAXtOXr6GUphoxHolEImlVZNArkUgkEolEIlnySE+vRCKRSCQSiWTJI4NeiUQikUgkEsmSRwa9EolEIpFIJJIljwx6JRKJRCKRSCRLnv8fRP0p2/fTQ/8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_stl(redeem['total_redeem_amt'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.4准备目标值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "      <th>ds</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>32488348</td>\n",
       "      <td>2013-07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>29037390</td>\n",
       "      <td>2013-07-02</td>\n",
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       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>27270770</td>\n",
       "      <td>2013-07-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>18321185</td>\n",
       "      <td>2013-07-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>11648749</td>\n",
       "      <td>2013-07-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>302194801</td>\n",
       "      <td>2014-08-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>245082751</td>\n",
       "      <td>2014-08-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>267554713</td>\n",
       "      <td>2014-08-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>199708772</td>\n",
       "      <td>2014-08-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>275090213</td>\n",
       "      <td>2014-08-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     y         ds\n",
       "report_date                      \n",
       "2013-07-01    32488348 2013-07-01\n",
       "2013-07-02    29037390 2013-07-02\n",
       "2013-07-03    27270770 2013-07-03\n",
       "2013-07-04    18321185 2013-07-04\n",
       "2013-07-05    11648749 2013-07-05\n",
       "...                ...        ...\n",
       "2014-08-27   302194801 2014-08-27\n",
       "2014-08-28   245082751 2014-08-28\n",
       "2014-08-29   267554713 2014-08-29\n",
       "2014-08-30   199708772 2014-08-30\n",
       "2014-08-31   275090213 2014-08-31\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#上面的 那个 purchase 中的字段 total_purchase_amt 今日总购买量 是我们要预测的一列\n",
    "#prophet模型里面有个保留字 ‘ds’\n",
    "purchase['ds']=purchase.index\n",
    "purchase.rename(columns={'total_purchase_amt':'y'},inplace=True)#给字段改个名字 把 total_purchase_amt 换成y\n",
    "purchase # 同时把那个时间给了保留字 ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2014-08-28</td>\n",
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       "      <th>2014-08-29</th>\n",
       "      <td>273756380</td>\n",
       "      <td>2014-08-29</td>\n",
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       "      <td>196374134</td>\n",
       "      <td>2014-08-30</td>\n",
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       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>292943033</td>\n",
       "      <td>2014-08-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     y         ds\n",
       "report_date                      \n",
       "2013-07-01     5525022 2013-07-01\n",
       "2013-07-02     2554548 2013-07-02\n",
       "2013-07-03     5953867 2013-07-03\n",
       "2013-07-04     6410729 2013-07-04\n",
       "2013-07-05     2763587 2013-07-05\n",
       "...                ...        ...\n",
       "2014-08-27   468164147 2014-08-27\n",
       "2014-08-28   297893861 2014-08-28\n",
       "2014-08-29   273756380 2014-08-29\n",
       "2014-08-30   196374134 2014-08-30\n",
       "2014-08-31   292943033 2014-08-31\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "redeem['ds']=redeem.index #同理也把这里的ds也给复制一下 prophet的保留字\n",
    "redeem.rename(columns={'total_redeem_amt':'y'},inplace=True)#同时也给这个名字要预测的字段  redeem 总赎回量(消费+转出) 也给更改一下名字\n",
    "redeem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2014-08-31</td>\n",
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       "<p>427 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             y         ds\n",
       "0     32488348 2013-07-01\n",
       "1     29037390 2013-07-02\n",
       "2     27270770 2013-07-03\n",
       "3     18321185 2013-07-04\n",
       "4     11648749 2013-07-05\n",
       "..         ...        ...\n",
       "422  302194801 2014-08-27\n",
       "423  245082751 2014-08-28\n",
       "424  267554713 2014-08-29\n",
       "425  199708772 2014-08-30\n",
       "426  275090213 2014-08-31\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#这个时候再把purchase redeem的索引给重新更改一下\n",
    "purchase=purchase.reset_index(drop=True)\n",
    "purchase#这样就把索引给还原了   同样可以做一下redeem的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
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       "      <th>423</th>\n",
       "      <td>297893861</td>\n",
       "      <td>2014-08-28</td>\n",
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       "      <th>424</th>\n",
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       "      <td>2014-08-31</td>\n",
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       "<p>427 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "             y         ds\n",
       "0      5525022 2013-07-01\n",
       "1      2554548 2013-07-02\n",
       "2      5953867 2013-07-03\n",
       "3      6410729 2013-07-04\n",
       "4      2763587 2013-07-05\n",
       "..         ...        ...\n",
       "422  468164147 2014-08-27\n",
       "423  297893861 2014-08-28\n",
       "424  273756380 2014-08-29\n",
       "425  196374134 2014-08-30\n",
       "426  292943033 2014-08-31\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "redeem=redeem.reset_index(drop=True)\n",
    "redeem#这样就把索引给还原了   同样可以做一下redeem的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3模型训练与预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1模型导入与拟合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7fc1c3277a50>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#模型训练prophet\n",
    "from fbprophet import Prophet#导入模型\n",
    "\n",
    "#构造Prophet模型  weekly_seasonality=True表示周期为周的季节性 n_changepoints=300指定突变点的个数\n",
    "model=Prophet(weekly_seasonality=True,seasonality_prior_scale=0.1,n_changepoints=100)\n",
    "model.fit(purchase)#训练拟合模型  这里是购买的那个数据 purchase"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2模型预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>additive_terms_upper</th>\n",
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       "      <th>weekly_upper</th>\n",
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       "      <th>multiplicative_terms_lower</th>\n",
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       "      <th>0</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>-1.712705e+06</td>\n",
       "      <td>-7.548810e+07</td>\n",
       "      <td>1.560277e+08</td>\n",
       "      <td>-1.712705e+06</td>\n",
       "      <td>-1.712705e+06</td>\n",
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       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.317251e+07</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-07-02</td>\n",
       "      <td>-7.723488e+05</td>\n",
       "      <td>-7.241106e+07</td>\n",
       "      <td>1.639201e+08</td>\n",
       "      <td>-7.723488e+05</td>\n",
       "      <td>-7.723488e+05</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.684573e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-07-03</td>\n",
       "      <td>1.680071e+05</td>\n",
       "      <td>-7.944685e+07</td>\n",
       "      <td>1.632584e+08</td>\n",
       "      <td>1.680071e+05</td>\n",
       "      <td>1.680071e+05</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.787217e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-07-04</td>\n",
       "      <td>1.108363e+06</td>\n",
       "      <td>-8.683495e+07</td>\n",
       "      <td>1.397996e+08</td>\n",
       "      <td>1.108363e+06</td>\n",
       "      <td>1.108363e+06</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.061216e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-07-05</td>\n",
       "      <td>2.048719e+06</td>\n",
       "      <td>-1.266772e+08</td>\n",
       "      <td>1.062781e+08</td>\n",
       "      <td>2.048719e+06</td>\n",
       "      <td>2.048719e+06</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.585303e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>2.002318e+08</td>\n",
       "      <td>6.885135e+07</td>\n",
       "      <td>3.000741e+08</td>\n",
       "      <td>1.975867e+08</td>\n",
       "      <td>2.028544e+08</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.823300e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>1.994848e+08</td>\n",
       "      <td>1.834643e+07</td>\n",
       "      <td>2.536822e+08</td>\n",
       "      <td>1.966965e+08</td>\n",
       "      <td>2.022325e+08</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.299395e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>1.987377e+08</td>\n",
       "      <td>1.574194e+07</td>\n",
       "      <td>2.529764e+08</td>\n",
       "      <td>1.958104e+08</td>\n",
       "      <td>2.016194e+08</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.364735e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>1.979907e+08</td>\n",
       "      <td>1.254996e+08</td>\n",
       "      <td>3.553188e+08</td>\n",
       "      <td>1.948640e+08</td>\n",
       "      <td>2.010268e+08</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.428759e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>1.972436e+08</td>\n",
       "      <td>1.384208e+08</td>\n",
       "      <td>3.503676e+08</td>\n",
       "      <td>1.939470e+08</td>\n",
       "      <td>2.004549e+08</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.448617e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>457 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         trend    yhat_lower    yhat_upper   trend_lower  \\\n",
       "0   2013-07-01 -1.712705e+06 -7.548810e+07  1.560277e+08 -1.712705e+06   \n",
       "1   2013-07-02 -7.723488e+05 -7.241106e+07  1.639201e+08 -7.723488e+05   \n",
       "2   2013-07-03  1.680071e+05 -7.944685e+07  1.632584e+08  1.680071e+05   \n",
       "3   2013-07-04  1.108363e+06 -8.683495e+07  1.397996e+08  1.108363e+06   \n",
       "4   2013-07-05  2.048719e+06 -1.266772e+08  1.062781e+08  2.048719e+06   \n",
       "..         ...           ...           ...           ...           ...   \n",
       "452 2014-09-26  2.002318e+08  6.885135e+07  3.000741e+08  1.975867e+08   \n",
       "453 2014-09-27  1.994848e+08  1.834643e+07  2.536822e+08  1.966965e+08   \n",
       "454 2014-09-28  1.987377e+08  1.574194e+07  2.529764e+08  1.958104e+08   \n",
       "455 2014-09-29  1.979907e+08  1.254996e+08  3.553188e+08  1.948640e+08   \n",
       "456 2014-09-30  1.972436e+08  1.384208e+08  3.503676e+08  1.939470e+08   \n",
       "\n",
       "      trend_upper  additive_terms  additive_terms_lower  additive_terms_upper  \\\n",
       "0   -1.712705e+06    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "1   -7.723488e+05    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "2    1.680071e+05    3.770417e+07          3.770417e+07          3.770417e+07   \n",
       "3    1.108363e+06    1.950379e+07          1.950379e+07          1.950379e+07   \n",
       "4    2.048719e+06   -1.790175e+07         -1.790175e+07         -1.790175e+07   \n",
       "..            ...             ...                   ...                   ...   \n",
       "452  2.028544e+08   -1.790175e+07         -1.790175e+07         -1.790175e+07   \n",
       "453  2.022325e+08   -6.954529e+07         -6.954529e+07         -6.954529e+07   \n",
       "454  2.016194e+08   -6.226422e+07         -6.226422e+07         -6.226422e+07   \n",
       "455  2.010268e+08    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "456  2.004549e+08    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "\n",
       "           weekly  weekly_lower  weekly_upper  multiplicative_terms  \\\n",
       "0    4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "1    4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "2    3.770417e+07  3.770417e+07  3.770417e+07                   0.0   \n",
       "3    1.950379e+07  1.950379e+07  1.950379e+07                   0.0   \n",
       "4   -1.790175e+07 -1.790175e+07 -1.790175e+07                   0.0   \n",
       "..            ...           ...           ...                   ...   \n",
       "452 -1.790175e+07 -1.790175e+07 -1.790175e+07                   0.0   \n",
       "453 -6.954529e+07 -6.954529e+07 -6.954529e+07                   0.0   \n",
       "454 -6.226422e+07 -6.226422e+07 -6.226422e+07                   0.0   \n",
       "455  4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "456  4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "\n",
       "     multiplicative_terms_lower  multiplicative_terms_upper          yhat  \n",
       "0                           0.0                         0.0  4.317251e+07  \n",
       "1                           0.0                         0.0  4.684573e+07  \n",
       "2                           0.0                         0.0  3.787217e+07  \n",
       "3                           0.0                         0.0  2.061216e+07  \n",
       "4                           0.0                         0.0 -1.585303e+07  \n",
       "..                          ...                         ...           ...  \n",
       "452                         0.0                         0.0  1.823300e+08  \n",
       "453                         0.0                         0.0  1.299395e+08  \n",
       "454                         0.0                         0.0  1.364735e+08  \n",
       "455                         0.0                         0.0  2.428759e+08  \n",
       "456                         0.0                         0.0  2.448617e+08  \n",
       "\n",
       "[457 rows x 16 columns]"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#预测未来1个月，9月份30天\n",
    "future=model.make_future_dataframe(periods=30)\n",
    "purchase_pred=model.predict(future)\n",
    "purchase_pred#propeht预测出来的是一个区间 这里下面有很多的参数  #这里是457行 因为原本的数据是427行数据  然后按照时序模型再预测了30天"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3预测结果可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_=model.plot(purchase_pred)#可视化一下 黑点是实际的点  蓝色的是我们预测出来的  感觉不是很准太平缓了 \n",
    "#plot方法会返回一个figure对象  如果不用一个变量接一下  这个图就显示两边"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>weekly</th>\n",
       "      <th>weekly_lower</th>\n",
       "      <th>weekly_upper</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>-1.888675e+07</td>\n",
       "      <td>-5.156628e+07</td>\n",
       "      <td>1.171973e+08</td>\n",
       "      <td>-1.888675e+07</td>\n",
       "      <td>-1.888675e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.022237e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-07-02</td>\n",
       "      <td>-1.809956e+07</td>\n",
       "      <td>-8.282254e+07</td>\n",
       "      <td>8.675654e+07</td>\n",
       "      <td>-1.809956e+07</td>\n",
       "      <td>-1.809956e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.713222e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-07-03</td>\n",
       "      <td>-1.731238e+07</td>\n",
       "      <td>-7.730108e+07</td>\n",
       "      <td>1.007860e+08</td>\n",
       "      <td>-1.731238e+07</td>\n",
       "      <td>-1.731238e+07</td>\n",
       "      <td>2.494285e+07</td>\n",
       "      <td>2.494285e+07</td>\n",
       "      <td>2.494285e+07</td>\n",
       "      <td>2.494285e+07</td>\n",
       "      <td>2.494285e+07</td>\n",
       "      <td>2.494285e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.630471e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-07-04</td>\n",
       "      <td>-1.652519e+07</td>\n",
       "      <td>-9.196723e+07</td>\n",
       "      <td>7.760850e+07</td>\n",
       "      <td>-1.652519e+07</td>\n",
       "      <td>-1.652519e+07</td>\n",
       "      <td>6.132402e+06</td>\n",
       "      <td>6.132402e+06</td>\n",
       "      <td>6.132402e+06</td>\n",
       "      <td>6.132402e+06</td>\n",
       "      <td>6.132402e+06</td>\n",
       "      <td>6.132402e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.039279e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-07-05</td>\n",
       "      <td>-1.573801e+07</td>\n",
       "      <td>-1.076688e+08</td>\n",
       "      <td>6.852256e+07</td>\n",
       "      <td>-1.573801e+07</td>\n",
       "      <td>-1.573801e+07</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.027585e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>2.918399e+08</td>\n",
       "      <td>2.018572e+08</td>\n",
       "      <td>3.720240e+08</td>\n",
       "      <td>2.907938e+08</td>\n",
       "      <td>2.928892e+08</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>-4.537845e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.873021e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>2.920113e+08</td>\n",
       "      <td>1.566447e+08</td>\n",
       "      <td>3.173192e+08</td>\n",
       "      <td>2.909127e+08</td>\n",
       "      <td>2.931378e+08</td>\n",
       "      <td>-5.860041e+07</td>\n",
       "      <td>-5.860041e+07</td>\n",
       "      <td>-5.860041e+07</td>\n",
       "      <td>-5.860041e+07</td>\n",
       "      <td>-5.860041e+07</td>\n",
       "      <td>-5.860041e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.334109e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>2.921827e+08</td>\n",
       "      <td>1.651961e+08</td>\n",
       "      <td>3.367961e+08</td>\n",
       "      <td>2.910254e+08</td>\n",
       "      <td>2.933840e+08</td>\n",
       "      <td>-3.985889e+07</td>\n",
       "      <td>-3.985889e+07</td>\n",
       "      <td>-3.985889e+07</td>\n",
       "      <td>-3.985889e+07</td>\n",
       "      <td>-3.985889e+07</td>\n",
       "      <td>-3.985889e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.523238e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>2.923541e+08</td>\n",
       "      <td>2.509004e+08</td>\n",
       "      <td>4.267793e+08</td>\n",
       "      <td>2.911238e+08</td>\n",
       "      <td>2.936131e+08</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>4.910912e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.414632e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>2.925254e+08</td>\n",
       "      <td>2.358115e+08</td>\n",
       "      <td>3.947936e+08</td>\n",
       "      <td>2.912352e+08</td>\n",
       "      <td>2.938672e+08</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>2.281278e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.153382e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>457 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         trend    yhat_lower    yhat_upper   trend_lower  \\\n",
       "0   2013-07-01 -1.888675e+07 -5.156628e+07  1.171973e+08 -1.888675e+07   \n",
       "1   2013-07-02 -1.809956e+07 -8.282254e+07  8.675654e+07 -1.809956e+07   \n",
       "2   2013-07-03 -1.731238e+07 -7.730108e+07  1.007860e+08 -1.731238e+07   \n",
       "3   2013-07-04 -1.652519e+07 -9.196723e+07  7.760850e+07 -1.652519e+07   \n",
       "4   2013-07-05 -1.573801e+07 -1.076688e+08  6.852256e+07 -1.573801e+07   \n",
       "..         ...           ...           ...           ...           ...   \n",
       "452 2014-09-26  2.918399e+08  2.018572e+08  3.720240e+08  2.907938e+08   \n",
       "453 2014-09-27  2.920113e+08  1.566447e+08  3.173192e+08  2.909127e+08   \n",
       "454 2014-09-28  2.921827e+08  1.651961e+08  3.367961e+08  2.910254e+08   \n",
       "455 2014-09-29  2.923541e+08  2.509004e+08  4.267793e+08  2.911238e+08   \n",
       "456 2014-09-30  2.925254e+08  2.358115e+08  3.947936e+08  2.912352e+08   \n",
       "\n",
       "      trend_upper  additive_terms  additive_terms_lower  additive_terms_upper  \\\n",
       "0   -1.888675e+07    4.910912e+07          4.910912e+07          4.910912e+07   \n",
       "1   -1.809956e+07    2.281278e+07          2.281278e+07          2.281278e+07   \n",
       "2   -1.731238e+07    2.494285e+07          2.494285e+07          2.494285e+07   \n",
       "3   -1.652519e+07    6.132402e+06          6.132402e+06          6.132402e+06   \n",
       "4   -1.573801e+07   -4.537845e+06         -4.537845e+06         -4.537845e+06   \n",
       "..            ...             ...                   ...                   ...   \n",
       "452  2.928892e+08   -4.537845e+06         -4.537845e+06         -4.537845e+06   \n",
       "453  2.931378e+08   -5.860041e+07         -5.860041e+07         -5.860041e+07   \n",
       "454  2.933840e+08   -3.985889e+07         -3.985889e+07         -3.985889e+07   \n",
       "455  2.936131e+08    4.910912e+07          4.910912e+07          4.910912e+07   \n",
       "456  2.938672e+08    2.281278e+07          2.281278e+07          2.281278e+07   \n",
       "\n",
       "           weekly  weekly_lower  weekly_upper  multiplicative_terms  \\\n",
       "0    4.910912e+07  4.910912e+07  4.910912e+07                   0.0   \n",
       "1    2.281278e+07  2.281278e+07  2.281278e+07                   0.0   \n",
       "2    2.494285e+07  2.494285e+07  2.494285e+07                   0.0   \n",
       "3    6.132402e+06  6.132402e+06  6.132402e+06                   0.0   \n",
       "4   -4.537845e+06 -4.537845e+06 -4.537845e+06                   0.0   \n",
       "..            ...           ...           ...                   ...   \n",
       "452 -4.537845e+06 -4.537845e+06 -4.537845e+06                   0.0   \n",
       "453 -5.860041e+07 -5.860041e+07 -5.860041e+07                   0.0   \n",
       "454 -3.985889e+07 -3.985889e+07 -3.985889e+07                   0.0   \n",
       "455  4.910912e+07  4.910912e+07  4.910912e+07                   0.0   \n",
       "456  2.281278e+07  2.281278e+07  2.281278e+07                   0.0   \n",
       "\n",
       "     multiplicative_terms_lower  multiplicative_terms_upper          yhat  \n",
       "0                           0.0                         0.0  3.022237e+07  \n",
       "1                           0.0                         0.0  4.713222e+06  \n",
       "2                           0.0                         0.0  7.630471e+06  \n",
       "3                           0.0                         0.0 -1.039279e+07  \n",
       "4                           0.0                         0.0 -2.027585e+07  \n",
       "..                          ...                         ...           ...  \n",
       "452                         0.0                         0.0  2.873021e+08  \n",
       "453                         0.0                         0.0  2.334109e+08  \n",
       "454                         0.0                         0.0  2.523238e+08  \n",
       "455                         0.0                         0.0  3.414632e+08  \n",
       "456                         0.0                         0.0  3.153382e+08  \n",
       "\n",
       "[457 rows x 16 columns]"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#同样可以做一下 redeem的拟合和预测\n",
    "model2=Prophet(weekly_seasonality=True,seasonality_prior_scale=0.1,n_changepoints=100)\n",
    "model2.fit(redeem)\n",
    "#预测未来1个月，9月份30天\n",
    "future=model2.make_future_dataframe(periods=30)\n",
    "redeem_pred=model2.predict(future)\n",
    "redeem_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_=model2.plot(redeem_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.4预测结果提交"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>weekly</th>\n",
       "      <th>weekly_lower</th>\n",
       "      <th>weekly_upper</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>2.189078e+08</td>\n",
       "      <td>1.528467e+08</td>\n",
       "      <td>3.811520e+08</td>\n",
       "      <td>2.189049e+08</td>\n",
       "      <td>2.189082e+08</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.637930e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>2014-09-02</td>\n",
       "      <td>2.181607e+08</td>\n",
       "      <td>1.482388e+08</td>\n",
       "      <td>3.820959e+08</td>\n",
       "      <td>2.181343e+08</td>\n",
       "      <td>2.181816e+08</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.657788e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>2014-09-03</td>\n",
       "      <td>2.174137e+08</td>\n",
       "      <td>1.438799e+08</td>\n",
       "      <td>3.763662e+08</td>\n",
       "      <td>2.173515e+08</td>\n",
       "      <td>2.174663e+08</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.551178e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>2014-09-04</td>\n",
       "      <td>2.166666e+08</td>\n",
       "      <td>1.185270e+08</td>\n",
       "      <td>3.576982e+08</td>\n",
       "      <td>2.165433e+08</td>\n",
       "      <td>2.167703e+08</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.361704e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>2014-09-05</td>\n",
       "      <td>2.159196e+08</td>\n",
       "      <td>8.083448e+07</td>\n",
       "      <td>3.124999e+08</td>\n",
       "      <td>2.157353e+08</td>\n",
       "      <td>2.160831e+08</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.980179e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>2014-09-06</td>\n",
       "      <td>2.151726e+08</td>\n",
       "      <td>1.885688e+07</td>\n",
       "      <td>2.589036e+08</td>\n",
       "      <td>2.149158e+08</td>\n",
       "      <td>2.154049e+08</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.456273e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>2.144255e+08</td>\n",
       "      <td>3.385889e+07</td>\n",
       "      <td>2.724886e+08</td>\n",
       "      <td>2.140765e+08</td>\n",
       "      <td>2.147418e+08</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.521613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>2014-09-08</td>\n",
       "      <td>2.136785e+08</td>\n",
       "      <td>1.406901e+08</td>\n",
       "      <td>3.673100e+08</td>\n",
       "      <td>2.132403e+08</td>\n",
       "      <td>2.140678e+08</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.585637e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>2014-09-09</td>\n",
       "      <td>2.129314e+08</td>\n",
       "      <td>1.425909e+08</td>\n",
       "      <td>3.765285e+08</td>\n",
       "      <td>2.124108e+08</td>\n",
       "      <td>2.134102e+08</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.605495e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2014-09-10</td>\n",
       "      <td>2.121844e+08</td>\n",
       "      <td>1.285290e+08</td>\n",
       "      <td>3.578615e+08</td>\n",
       "      <td>2.115555e+08</td>\n",
       "      <td>2.127562e+08</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.498886e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2014-09-11</td>\n",
       "      <td>2.114374e+08</td>\n",
       "      <td>1.110797e+08</td>\n",
       "      <td>3.468252e+08</td>\n",
       "      <td>2.106927e+08</td>\n",
       "      <td>2.121056e+08</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.309412e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2014-09-12</td>\n",
       "      <td>2.106903e+08</td>\n",
       "      <td>6.889568e+07</td>\n",
       "      <td>3.155314e+08</td>\n",
       "      <td>2.098285e+08</td>\n",
       "      <td>2.114583e+08</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.927886e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2014-09-13</td>\n",
       "      <td>2.099433e+08</td>\n",
       "      <td>1.780752e+07</td>\n",
       "      <td>2.630076e+08</td>\n",
       "      <td>2.089669e+08</td>\n",
       "      <td>2.108107e+08</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.403980e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2014-09-14</td>\n",
       "      <td>2.091963e+08</td>\n",
       "      <td>2.657177e+07</td>\n",
       "      <td>2.567758e+08</td>\n",
       "      <td>2.081114e+08</td>\n",
       "      <td>2.101884e+08</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.469320e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>2014-09-15</td>\n",
       "      <td>2.084492e+08</td>\n",
       "      <td>1.449774e+08</td>\n",
       "      <td>3.703551e+08</td>\n",
       "      <td>2.072636e+08</td>\n",
       "      <td>2.095538e+08</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.533344e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>2014-09-16</td>\n",
       "      <td>2.077022e+08</td>\n",
       "      <td>1.343108e+08</td>\n",
       "      <td>3.754779e+08</td>\n",
       "      <td>2.063913e+08</td>\n",
       "      <td>2.089358e+08</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.553203e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>2.069551e+08</td>\n",
       "      <td>1.266397e+08</td>\n",
       "      <td>3.663022e+08</td>\n",
       "      <td>2.055381e+08</td>\n",
       "      <td>2.083210e+08</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.446593e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>2.062081e+08</td>\n",
       "      <td>1.067557e+08</td>\n",
       "      <td>3.423115e+08</td>\n",
       "      <td>2.046529e+08</td>\n",
       "      <td>2.077133e+08</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.257119e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>2.054611e+08</td>\n",
       "      <td>7.804370e+07</td>\n",
       "      <td>3.112669e+08</td>\n",
       "      <td>2.037595e+08</td>\n",
       "      <td>2.071197e+08</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.875593e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>2.047140e+08</td>\n",
       "      <td>1.325640e+07</td>\n",
       "      <td>2.483199e+08</td>\n",
       "      <td>2.028952e+08</td>\n",
       "      <td>2.065254e+08</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.351687e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>2.039670e+08</td>\n",
       "      <td>2.628928e+07</td>\n",
       "      <td>2.643726e+08</td>\n",
       "      <td>2.020123e+08</td>\n",
       "      <td>2.059195e+08</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.417028e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2.032199e+08</td>\n",
       "      <td>1.292694e+08</td>\n",
       "      <td>3.643039e+08</td>\n",
       "      <td>2.011184e+08</td>\n",
       "      <td>2.053082e+08</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.481052e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>2.024729e+08</td>\n",
       "      <td>1.355238e+08</td>\n",
       "      <td>3.683791e+08</td>\n",
       "      <td>2.002448e+08</td>\n",
       "      <td>2.047562e+08</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.500910e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>2014-09-24</td>\n",
       "      <td>2.017259e+08</td>\n",
       "      <td>1.253407e+08</td>\n",
       "      <td>3.581360e+08</td>\n",
       "      <td>1.993669e+08</td>\n",
       "      <td>2.041149e+08</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>3.770417e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.394300e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>2014-09-25</td>\n",
       "      <td>2.009788e+08</td>\n",
       "      <td>9.875172e+07</td>\n",
       "      <td>3.377357e+08</td>\n",
       "      <td>1.984904e+08</td>\n",
       "      <td>2.034711e+08</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>1.950379e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.204826e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>2.002318e+08</td>\n",
       "      <td>6.885135e+07</td>\n",
       "      <td>3.000741e+08</td>\n",
       "      <td>1.975867e+08</td>\n",
       "      <td>2.028544e+08</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>-1.790175e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.823300e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>1.994848e+08</td>\n",
       "      <td>1.834643e+07</td>\n",
       "      <td>2.536822e+08</td>\n",
       "      <td>1.966965e+08</td>\n",
       "      <td>2.022325e+08</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>-6.954529e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.299395e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>1.987377e+08</td>\n",
       "      <td>1.574194e+07</td>\n",
       "      <td>2.529764e+08</td>\n",
       "      <td>1.958104e+08</td>\n",
       "      <td>2.016194e+08</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>-6.226422e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.364735e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>1.979907e+08</td>\n",
       "      <td>1.254996e+08</td>\n",
       "      <td>3.553188e+08</td>\n",
       "      <td>1.948640e+08</td>\n",
       "      <td>2.010268e+08</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>4.488522e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.428759e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>1.972436e+08</td>\n",
       "      <td>1.384208e+08</td>\n",
       "      <td>3.503676e+08</td>\n",
       "      <td>1.939470e+08</td>\n",
       "      <td>2.004549e+08</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>4.761808e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.448617e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         trend    yhat_lower    yhat_upper   trend_lower  \\\n",
       "427 2014-09-01  2.189078e+08  1.528467e+08  3.811520e+08  2.189049e+08   \n",
       "428 2014-09-02  2.181607e+08  1.482388e+08  3.820959e+08  2.181343e+08   \n",
       "429 2014-09-03  2.174137e+08  1.438799e+08  3.763662e+08  2.173515e+08   \n",
       "430 2014-09-04  2.166666e+08  1.185270e+08  3.576982e+08  2.165433e+08   \n",
       "431 2014-09-05  2.159196e+08  8.083448e+07  3.124999e+08  2.157353e+08   \n",
       "432 2014-09-06  2.151726e+08  1.885688e+07  2.589036e+08  2.149158e+08   \n",
       "433 2014-09-07  2.144255e+08  3.385889e+07  2.724886e+08  2.140765e+08   \n",
       "434 2014-09-08  2.136785e+08  1.406901e+08  3.673100e+08  2.132403e+08   \n",
       "435 2014-09-09  2.129314e+08  1.425909e+08  3.765285e+08  2.124108e+08   \n",
       "436 2014-09-10  2.121844e+08  1.285290e+08  3.578615e+08  2.115555e+08   \n",
       "437 2014-09-11  2.114374e+08  1.110797e+08  3.468252e+08  2.106927e+08   \n",
       "438 2014-09-12  2.106903e+08  6.889568e+07  3.155314e+08  2.098285e+08   \n",
       "439 2014-09-13  2.099433e+08  1.780752e+07  2.630076e+08  2.089669e+08   \n",
       "440 2014-09-14  2.091963e+08  2.657177e+07  2.567758e+08  2.081114e+08   \n",
       "441 2014-09-15  2.084492e+08  1.449774e+08  3.703551e+08  2.072636e+08   \n",
       "442 2014-09-16  2.077022e+08  1.343108e+08  3.754779e+08  2.063913e+08   \n",
       "443 2014-09-17  2.069551e+08  1.266397e+08  3.663022e+08  2.055381e+08   \n",
       "444 2014-09-18  2.062081e+08  1.067557e+08  3.423115e+08  2.046529e+08   \n",
       "445 2014-09-19  2.054611e+08  7.804370e+07  3.112669e+08  2.037595e+08   \n",
       "446 2014-09-20  2.047140e+08  1.325640e+07  2.483199e+08  2.028952e+08   \n",
       "447 2014-09-21  2.039670e+08  2.628928e+07  2.643726e+08  2.020123e+08   \n",
       "448 2014-09-22  2.032199e+08  1.292694e+08  3.643039e+08  2.011184e+08   \n",
       "449 2014-09-23  2.024729e+08  1.355238e+08  3.683791e+08  2.002448e+08   \n",
       "450 2014-09-24  2.017259e+08  1.253407e+08  3.581360e+08  1.993669e+08   \n",
       "451 2014-09-25  2.009788e+08  9.875172e+07  3.377357e+08  1.984904e+08   \n",
       "452 2014-09-26  2.002318e+08  6.885135e+07  3.000741e+08  1.975867e+08   \n",
       "453 2014-09-27  1.994848e+08  1.834643e+07  2.536822e+08  1.966965e+08   \n",
       "454 2014-09-28  1.987377e+08  1.574194e+07  2.529764e+08  1.958104e+08   \n",
       "455 2014-09-29  1.979907e+08  1.254996e+08  3.553188e+08  1.948640e+08   \n",
       "456 2014-09-30  1.972436e+08  1.384208e+08  3.503676e+08  1.939470e+08   \n",
       "\n",
       "      trend_upper  additive_terms  additive_terms_lower  additive_terms_upper  \\\n",
       "427  2.189082e+08    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "428  2.181816e+08    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "429  2.174663e+08    3.770417e+07          3.770417e+07          3.770417e+07   \n",
       "430  2.167703e+08    1.950379e+07          1.950379e+07          1.950379e+07   \n",
       "431  2.160831e+08   -1.790175e+07         -1.790175e+07         -1.790175e+07   \n",
       "432  2.154049e+08   -6.954529e+07         -6.954529e+07         -6.954529e+07   \n",
       "433  2.147418e+08   -6.226422e+07         -6.226422e+07         -6.226422e+07   \n",
       "434  2.140678e+08    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "435  2.134102e+08    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "436  2.127562e+08    3.770417e+07          3.770417e+07          3.770417e+07   \n",
       "437  2.121056e+08    1.950379e+07          1.950379e+07          1.950379e+07   \n",
       "438  2.114583e+08   -1.790175e+07         -1.790175e+07         -1.790175e+07   \n",
       "439  2.108107e+08   -6.954529e+07         -6.954529e+07         -6.954529e+07   \n",
       "440  2.101884e+08   -6.226422e+07         -6.226422e+07         -6.226422e+07   \n",
       "441  2.095538e+08    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "442  2.089358e+08    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "443  2.083210e+08    3.770417e+07          3.770417e+07          3.770417e+07   \n",
       "444  2.077133e+08    1.950379e+07          1.950379e+07          1.950379e+07   \n",
       "445  2.071197e+08   -1.790175e+07         -1.790175e+07         -1.790175e+07   \n",
       "446  2.065254e+08   -6.954529e+07         -6.954529e+07         -6.954529e+07   \n",
       "447  2.059195e+08   -6.226422e+07         -6.226422e+07         -6.226422e+07   \n",
       "448  2.053082e+08    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "449  2.047562e+08    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "450  2.041149e+08    3.770417e+07          3.770417e+07          3.770417e+07   \n",
       "451  2.034711e+08    1.950379e+07          1.950379e+07          1.950379e+07   \n",
       "452  2.028544e+08   -1.790175e+07         -1.790175e+07         -1.790175e+07   \n",
       "453  2.022325e+08   -6.954529e+07         -6.954529e+07         -6.954529e+07   \n",
       "454  2.016194e+08   -6.226422e+07         -6.226422e+07         -6.226422e+07   \n",
       "455  2.010268e+08    4.488522e+07          4.488522e+07          4.488522e+07   \n",
       "456  2.004549e+08    4.761808e+07          4.761808e+07          4.761808e+07   \n",
       "\n",
       "           weekly  weekly_lower  weekly_upper  multiplicative_terms  \\\n",
       "427  4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "428  4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "429  3.770417e+07  3.770417e+07  3.770417e+07                   0.0   \n",
       "430  1.950379e+07  1.950379e+07  1.950379e+07                   0.0   \n",
       "431 -1.790175e+07 -1.790175e+07 -1.790175e+07                   0.0   \n",
       "432 -6.954529e+07 -6.954529e+07 -6.954529e+07                   0.0   \n",
       "433 -6.226422e+07 -6.226422e+07 -6.226422e+07                   0.0   \n",
       "434  4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "435  4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "436  3.770417e+07  3.770417e+07  3.770417e+07                   0.0   \n",
       "437  1.950379e+07  1.950379e+07  1.950379e+07                   0.0   \n",
       "438 -1.790175e+07 -1.790175e+07 -1.790175e+07                   0.0   \n",
       "439 -6.954529e+07 -6.954529e+07 -6.954529e+07                   0.0   \n",
       "440 -6.226422e+07 -6.226422e+07 -6.226422e+07                   0.0   \n",
       "441  4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "442  4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "443  3.770417e+07  3.770417e+07  3.770417e+07                   0.0   \n",
       "444  1.950379e+07  1.950379e+07  1.950379e+07                   0.0   \n",
       "445 -1.790175e+07 -1.790175e+07 -1.790175e+07                   0.0   \n",
       "446 -6.954529e+07 -6.954529e+07 -6.954529e+07                   0.0   \n",
       "447 -6.226422e+07 -6.226422e+07 -6.226422e+07                   0.0   \n",
       "448  4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "449  4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "450  3.770417e+07  3.770417e+07  3.770417e+07                   0.0   \n",
       "451  1.950379e+07  1.950379e+07  1.950379e+07                   0.0   \n",
       "452 -1.790175e+07 -1.790175e+07 -1.790175e+07                   0.0   \n",
       "453 -6.954529e+07 -6.954529e+07 -6.954529e+07                   0.0   \n",
       "454 -6.226422e+07 -6.226422e+07 -6.226422e+07                   0.0   \n",
       "455  4.488522e+07  4.488522e+07  4.488522e+07                   0.0   \n",
       "456  4.761808e+07  4.761808e+07  4.761808e+07                   0.0   \n",
       "\n",
       "     multiplicative_terms_lower  multiplicative_terms_upper          yhat  \n",
       "427                         0.0                         0.0  2.637930e+08  \n",
       "428                         0.0                         0.0  2.657788e+08  \n",
       "429                         0.0                         0.0  2.551178e+08  \n",
       "430                         0.0                         0.0  2.361704e+08  \n",
       "431                         0.0                         0.0  1.980179e+08  \n",
       "432                         0.0                         0.0  1.456273e+08  \n",
       "433                         0.0                         0.0  1.521613e+08  \n",
       "434                         0.0                         0.0  2.585637e+08  \n",
       "435                         0.0                         0.0  2.605495e+08  \n",
       "436                         0.0                         0.0  2.498886e+08  \n",
       "437                         0.0                         0.0  2.309412e+08  \n",
       "438                         0.0                         0.0  1.927886e+08  \n",
       "439                         0.0                         0.0  1.403980e+08  \n",
       "440                         0.0                         0.0  1.469320e+08  \n",
       "441                         0.0                         0.0  2.533344e+08  \n",
       "442                         0.0                         0.0  2.553203e+08  \n",
       "443                         0.0                         0.0  2.446593e+08  \n",
       "444                         0.0                         0.0  2.257119e+08  \n",
       "445                         0.0                         0.0  1.875593e+08  \n",
       "446                         0.0                         0.0  1.351687e+08  \n",
       "447                         0.0                         0.0  1.417028e+08  \n",
       "448                         0.0                         0.0  2.481052e+08  \n",
       "449                         0.0                         0.0  2.500910e+08  \n",
       "450                         0.0                         0.0  2.394300e+08  \n",
       "451                         0.0                         0.0  2.204826e+08  \n",
       "452                         0.0                         0.0  1.823300e+08  \n",
       "453                         0.0                         0.0  1.299395e+08  \n",
       "454                         0.0                         0.0  1.364735e+08  \n",
       "455                         0.0                         0.0  2.428759e+08  \n",
       "456                         0.0                         0.0  2.448617e+08  "
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#预测结果有了 然后筛选一下  作为结果输出  这个是总购买量的预测 预测指定的时间 就是下一个月 \n",
    "purchase_pred[(purchase_pred['ds']>='2014-09-01')&(purchase_pred['ds']<='2014-09-30')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>2.637930e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>2014-09-02</td>\n",
       "      <td>2.657788e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>2014-09-03</td>\n",
       "      <td>2.551178e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>2014-09-04</td>\n",
       "      <td>2.361704e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>2014-09-05</td>\n",
       "      <td>1.980179e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>2014-09-06</td>\n",
       "      <td>1.456273e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>1.521613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>2014-09-08</td>\n",
       "      <td>2.585637e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>2014-09-09</td>\n",
       "      <td>2.605495e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2014-09-10</td>\n",
       "      <td>2.498886e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2014-09-11</td>\n",
       "      <td>2.309412e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2014-09-12</td>\n",
       "      <td>1.927886e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2014-09-13</td>\n",
       "      <td>1.403980e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2014-09-14</td>\n",
       "      <td>1.469320e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>2014-09-15</td>\n",
       "      <td>2.533344e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>2014-09-16</td>\n",
       "      <td>2.553203e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>2.446593e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>2.257119e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>1.875593e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>1.351687e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>1.417028e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2.481052e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>2.500910e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>2014-09-24</td>\n",
       "      <td>2.394300e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>2014-09-25</td>\n",
       "      <td>2.204826e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>1.823300e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>1.299395e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>1.364735e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>2.428759e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>2.448617e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds          yhat\n",
       "427 2014-09-01  2.637930e+08\n",
       "428 2014-09-02  2.657788e+08\n",
       "429 2014-09-03  2.551178e+08\n",
       "430 2014-09-04  2.361704e+08\n",
       "431 2014-09-05  1.980179e+08\n",
       "432 2014-09-06  1.456273e+08\n",
       "433 2014-09-07  1.521613e+08\n",
       "434 2014-09-08  2.585637e+08\n",
       "435 2014-09-09  2.605495e+08\n",
       "436 2014-09-10  2.498886e+08\n",
       "437 2014-09-11  2.309412e+08\n",
       "438 2014-09-12  1.927886e+08\n",
       "439 2014-09-13  1.403980e+08\n",
       "440 2014-09-14  1.469320e+08\n",
       "441 2014-09-15  2.533344e+08\n",
       "442 2014-09-16  2.553203e+08\n",
       "443 2014-09-17  2.446593e+08\n",
       "444 2014-09-18  2.257119e+08\n",
       "445 2014-09-19  1.875593e+08\n",
       "446 2014-09-20  1.351687e+08\n",
       "447 2014-09-21  1.417028e+08\n",
       "448 2014-09-22  2.481052e+08\n",
       "449 2014-09-23  2.500910e+08\n",
       "450 2014-09-24  2.394300e+08\n",
       "451 2014-09-25  2.204826e+08\n",
       "452 2014-09-26  1.823300e+08\n",
       "453 2014-09-27  1.299395e+08\n",
       "454 2014-09-28  1.364735e+08\n",
       "455 2014-09-29  2.428759e+08\n",
       "456 2014-09-30  2.448617e+08"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#用一个结果存储一下 \n",
    "purchase2=purchase_pred[(purchase_pred['ds']>='2014-09-01')&(purchase_pred['ds']<='2014-09-30')][['ds','yhat']]#ds是时间列 yhat是预测值\n",
    "purchase2#这个是总购买量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>428</th>\n",
       "      <td>2014-09-02</td>\n",
       "      <td>3.105398e+08</td>\n",
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       "      <th>429</th>\n",
       "      <td>2014-09-03</td>\n",
       "      <td>3.128412e+08</td>\n",
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       "      <th>430</th>\n",
       "      <td>2014-09-04</td>\n",
       "      <td>2.942022e+08</td>\n",
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       "      <th>431</th>\n",
       "      <td>2014-09-05</td>\n",
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       "      <th>432</th>\n",
       "      <td>2014-09-06</td>\n",
       "      <td>2.298121e+08</td>\n",
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       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>2.487250e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>2014-09-08</td>\n",
       "      <td>3.378644e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>2014-09-09</td>\n",
       "      <td>3.117394e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2014-09-10</td>\n",
       "      <td>3.140408e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2014-09-11</td>\n",
       "      <td>2.954018e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2014-09-12</td>\n",
       "      <td>2.849029e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2014-09-13</td>\n",
       "      <td>2.310117e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2014-09-14</td>\n",
       "      <td>2.499246e+08</td>\n",
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       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>2014-09-15</td>\n",
       "      <td>3.390640e+08</td>\n",
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       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>2014-09-16</td>\n",
       "      <td>3.129390e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>3.152404e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>2.966014e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>2.861025e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>2.322113e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>2.511242e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>3.402636e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>3.141386e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>2014-09-24</td>\n",
       "      <td>3.164401e+08</td>\n",
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       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>2014-09-25</td>\n",
       "      <td>2.978010e+08</td>\n",
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       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>2.873021e+08</td>\n",
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       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>2.334109e+08</td>\n",
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       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>2.523238e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>3.414632e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>3.153382e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds          yhat\n",
       "427 2014-09-01  3.366648e+08\n",
       "428 2014-09-02  3.105398e+08\n",
       "429 2014-09-03  3.128412e+08\n",
       "430 2014-09-04  2.942022e+08\n",
       "431 2014-09-05  2.837033e+08\n",
       "432 2014-09-06  2.298121e+08\n",
       "433 2014-09-07  2.487250e+08\n",
       "434 2014-09-08  3.378644e+08\n",
       "435 2014-09-09  3.117394e+08\n",
       "436 2014-09-10  3.140408e+08\n",
       "437 2014-09-11  2.954018e+08\n",
       "438 2014-09-12  2.849029e+08\n",
       "439 2014-09-13  2.310117e+08\n",
       "440 2014-09-14  2.499246e+08\n",
       "441 2014-09-15  3.390640e+08\n",
       "442 2014-09-16  3.129390e+08\n",
       "443 2014-09-17  3.152404e+08\n",
       "444 2014-09-18  2.966014e+08\n",
       "445 2014-09-19  2.861025e+08\n",
       "446 2014-09-20  2.322113e+08\n",
       "447 2014-09-21  2.511242e+08\n",
       "448 2014-09-22  3.402636e+08\n",
       "449 2014-09-23  3.141386e+08\n",
       "450 2014-09-24  3.164401e+08\n",
       "451 2014-09-25  2.978010e+08\n",
       "452 2014-09-26  2.873021e+08\n",
       "453 2014-09-27  2.334109e+08\n",
       "454 2014-09-28  2.523238e+08\n",
       "455 2014-09-29  3.414632e+08\n",
       "456 2014-09-30  3.153382e+08"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "redeem2=redeem_pred[(redeem_pred['ds']>='2014-09-01')&(redeem_pred['ds']<='2014-09-30')][['ds','yhat']]\n",
    "redeem2#z这个是总赎回量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
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       "    <tr>\n",
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       "      <td>2014-09-09</td>\n",
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       "      <td>3.117394e+08</td>\n",
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       "    <tr>\n",
       "      <th>436</th>\n",
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       "      <td>2.498886e+08</td>\n",
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       "      <td>2.309412e+08</td>\n",
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       "      <td>1.403980e+08</td>\n",
       "      <td>2.310117e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2014-09-14</td>\n",
       "      <td>1.469320e+08</td>\n",
       "      <td>2.499246e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>2014-09-15</td>\n",
       "      <td>2.533344e+08</td>\n",
       "      <td>3.390640e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>2014-09-16</td>\n",
       "      <td>2.553203e+08</td>\n",
       "      <td>3.129390e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>2.446593e+08</td>\n",
       "      <td>3.152404e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>2.257119e+08</td>\n",
       "      <td>2.966014e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>1.875593e+08</td>\n",
       "      <td>2.861025e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>1.351687e+08</td>\n",
       "      <td>2.322113e+08</td>\n",
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       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>1.417028e+08</td>\n",
       "      <td>2.511242e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2.481052e+08</td>\n",
       "      <td>3.402636e+08</td>\n",
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       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>2.500910e+08</td>\n",
       "      <td>3.141386e+08</td>\n",
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       "      <td>2.204826e+08</td>\n",
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       "      <th>452</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>1.823300e+08</td>\n",
       "      <td>2.873021e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>1.299395e+08</td>\n",
       "      <td>2.334109e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>1.364735e+08</td>\n",
       "      <td>2.523238e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>2.428759e+08</td>\n",
       "      <td>3.414632e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>2.448617e+08</td>\n",
       "      <td>3.153382e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds  purchase_amt    redeem_amt\n",
       "427 2014-09-01  2.637930e+08  3.366648e+08\n",
       "428 2014-09-02  2.657788e+08  3.105398e+08\n",
       "429 2014-09-03  2.551178e+08  3.128412e+08\n",
       "430 2014-09-04  2.361704e+08  2.942022e+08\n",
       "431 2014-09-05  1.980179e+08  2.837033e+08\n",
       "432 2014-09-06  1.456273e+08  2.298121e+08\n",
       "433 2014-09-07  1.521613e+08  2.487250e+08\n",
       "434 2014-09-08  2.585637e+08  3.378644e+08\n",
       "435 2014-09-09  2.605495e+08  3.117394e+08\n",
       "436 2014-09-10  2.498886e+08  3.140408e+08\n",
       "437 2014-09-11  2.309412e+08  2.954018e+08\n",
       "438 2014-09-12  1.927886e+08  2.849029e+08\n",
       "439 2014-09-13  1.403980e+08  2.310117e+08\n",
       "440 2014-09-14  1.469320e+08  2.499246e+08\n",
       "441 2014-09-15  2.533344e+08  3.390640e+08\n",
       "442 2014-09-16  2.553203e+08  3.129390e+08\n",
       "443 2014-09-17  2.446593e+08  3.152404e+08\n",
       "444 2014-09-18  2.257119e+08  2.966014e+08\n",
       "445 2014-09-19  1.875593e+08  2.861025e+08\n",
       "446 2014-09-20  1.351687e+08  2.322113e+08\n",
       "447 2014-09-21  1.417028e+08  2.511242e+08\n",
       "448 2014-09-22  2.481052e+08  3.402636e+08\n",
       "449 2014-09-23  2.500910e+08  3.141386e+08\n",
       "450 2014-09-24  2.394300e+08  3.164401e+08\n",
       "451 2014-09-25  2.204826e+08  2.978010e+08\n",
       "452 2014-09-26  1.823300e+08  2.873021e+08\n",
       "453 2014-09-27  1.299395e+08  2.334109e+08\n",
       "454 2014-09-28  1.364735e+08  2.523238e+08\n",
       "455 2014-09-29  2.428759e+08  3.414632e+08\n",
       "456 2014-09-30  2.448617e+08  3.153382e+08"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#合并拼接结果\n",
    "result=pd.DataFrame()#一个空的df\n",
    "result['ds']=purchase2['ds']#然后把时间放进去\n",
    "result['purchase_amt']=purchase2['yhat']#把总购买量放进去  \n",
    "result['redeem_amt']=redeem2['yhat']#把总赎回量放进去\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_csv('n_prophet.csv',header=None,index=False)#这样直接提交结果是不正确的 因为不符合题目的要求 要把日期中间的'-'给去掉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>purchase_amt</th>\n",
       "      <th>redeem_amt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>20140901 00:00:00</td>\n",
       "      <td>2.637930e+08</td>\n",
       "      <td>3.366648e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>20140902 00:00:00</td>\n",
       "      <td>2.657788e+08</td>\n",
       "      <td>3.105398e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>20140903 00:00:00</td>\n",
       "      <td>2.551178e+08</td>\n",
       "      <td>3.128412e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>20140904 00:00:00</td>\n",
       "      <td>2.361704e+08</td>\n",
       "      <td>2.942022e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>20140905 00:00:00</td>\n",
       "      <td>1.980179e+08</td>\n",
       "      <td>2.837033e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>20140906 00:00:00</td>\n",
       "      <td>1.456273e+08</td>\n",
       "      <td>2.298121e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>20140907 00:00:00</td>\n",
       "      <td>1.521613e+08</td>\n",
       "      <td>2.487250e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>20140908 00:00:00</td>\n",
       "      <td>2.585637e+08</td>\n",
       "      <td>3.378644e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>20140909 00:00:00</td>\n",
       "      <td>2.605495e+08</td>\n",
       "      <td>3.117394e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>20140910 00:00:00</td>\n",
       "      <td>2.498886e+08</td>\n",
       "      <td>3.140408e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>20140911 00:00:00</td>\n",
       "      <td>2.309412e+08</td>\n",
       "      <td>2.954018e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>20140912 00:00:00</td>\n",
       "      <td>1.927886e+08</td>\n",
       "      <td>2.849029e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>20140913 00:00:00</td>\n",
       "      <td>1.403980e+08</td>\n",
       "      <td>2.310117e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>20140914 00:00:00</td>\n",
       "      <td>1.469320e+08</td>\n",
       "      <td>2.499246e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>20140915 00:00:00</td>\n",
       "      <td>2.533344e+08</td>\n",
       "      <td>3.390640e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>20140916 00:00:00</td>\n",
       "      <td>2.553203e+08</td>\n",
       "      <td>3.129390e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>20140917 00:00:00</td>\n",
       "      <td>2.446593e+08</td>\n",
       "      <td>3.152404e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>20140918 00:00:00</td>\n",
       "      <td>2.257119e+08</td>\n",
       "      <td>2.966014e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>20140919 00:00:00</td>\n",
       "      <td>1.875593e+08</td>\n",
       "      <td>2.861025e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>20140920 00:00:00</td>\n",
       "      <td>1.351687e+08</td>\n",
       "      <td>2.322113e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>20140921 00:00:00</td>\n",
       "      <td>1.417028e+08</td>\n",
       "      <td>2.511242e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>20140922 00:00:00</td>\n",
       "      <td>2.481052e+08</td>\n",
       "      <td>3.402636e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>20140923 00:00:00</td>\n",
       "      <td>2.500910e+08</td>\n",
       "      <td>3.141386e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>20140924 00:00:00</td>\n",
       "      <td>2.394300e+08</td>\n",
       "      <td>3.164401e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>20140925 00:00:00</td>\n",
       "      <td>2.204826e+08</td>\n",
       "      <td>2.978010e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>20140926 00:00:00</td>\n",
       "      <td>1.823300e+08</td>\n",
       "      <td>2.873021e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>20140927 00:00:00</td>\n",
       "      <td>1.299395e+08</td>\n",
       "      <td>2.334109e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>20140928 00:00:00</td>\n",
       "      <td>1.364735e+08</td>\n",
       "      <td>2.523238e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>20140929 00:00:00</td>\n",
       "      <td>2.428759e+08</td>\n",
       "      <td>3.414632e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>20140930 00:00:00</td>\n",
       "      <td>2.448617e+08</td>\n",
       "      <td>3.153382e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    ds  purchase_amt    redeem_amt\n",
       "427  20140901 00:00:00  2.637930e+08  3.366648e+08\n",
       "428  20140902 00:00:00  2.657788e+08  3.105398e+08\n",
       "429  20140903 00:00:00  2.551178e+08  3.128412e+08\n",
       "430  20140904 00:00:00  2.361704e+08  2.942022e+08\n",
       "431  20140905 00:00:00  1.980179e+08  2.837033e+08\n",
       "432  20140906 00:00:00  1.456273e+08  2.298121e+08\n",
       "433  20140907 00:00:00  1.521613e+08  2.487250e+08\n",
       "434  20140908 00:00:00  2.585637e+08  3.378644e+08\n",
       "435  20140909 00:00:00  2.605495e+08  3.117394e+08\n",
       "436  20140910 00:00:00  2.498886e+08  3.140408e+08\n",
       "437  20140911 00:00:00  2.309412e+08  2.954018e+08\n",
       "438  20140912 00:00:00  1.927886e+08  2.849029e+08\n",
       "439  20140913 00:00:00  1.403980e+08  2.310117e+08\n",
       "440  20140914 00:00:00  1.469320e+08  2.499246e+08\n",
       "441  20140915 00:00:00  2.533344e+08  3.390640e+08\n",
       "442  20140916 00:00:00  2.553203e+08  3.129390e+08\n",
       "443  20140917 00:00:00  2.446593e+08  3.152404e+08\n",
       "444  20140918 00:00:00  2.257119e+08  2.966014e+08\n",
       "445  20140919 00:00:00  1.875593e+08  2.861025e+08\n",
       "446  20140920 00:00:00  1.351687e+08  2.322113e+08\n",
       "447  20140921 00:00:00  1.417028e+08  2.511242e+08\n",
       "448  20140922 00:00:00  2.481052e+08  3.402636e+08\n",
       "449  20140923 00:00:00  2.500910e+08  3.141386e+08\n",
       "450  20140924 00:00:00  2.394300e+08  3.164401e+08\n",
       "451  20140925 00:00:00  2.204826e+08  2.978010e+08\n",
       "452  20140926 00:00:00  1.823300e+08  2.873021e+08\n",
       "453  20140927 00:00:00  1.299395e+08  2.334109e+08\n",
       "454  20140928 00:00:00  1.364735e+08  2.523238e+08\n",
       "455  20140929 00:00:00  2.428759e+08  3.414632e+08\n",
       "456  20140930 00:00:00  2.448617e+08  3.153382e+08"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result['ds']=result['ds'].apply(lambda x:str(x).replace('-',''))\n",
    "result\n",
    "# result#这样做 后面的0000000都显示出来了  不需要  所以只需要前8位"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
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       "      <th>428</th>\n",
       "      <td>20140902</td>\n",
       "      <td>2.657788e+08</td>\n",
       "      <td>3.105398e+08</td>\n",
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       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>20140903</td>\n",
       "      <td>2.551178e+08</td>\n",
       "      <td>3.128412e+08</td>\n",
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       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>20140904</td>\n",
       "      <td>2.361704e+08</td>\n",
       "      <td>2.942022e+08</td>\n",
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       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>20140905</td>\n",
       "      <td>1.980179e+08</td>\n",
       "      <td>2.837033e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>20140906</td>\n",
       "      <td>1.456273e+08</td>\n",
       "      <td>2.298121e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>20140907</td>\n",
       "      <td>1.521613e+08</td>\n",
       "      <td>2.487250e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>20140908</td>\n",
       "      <td>2.585637e+08</td>\n",
       "      <td>3.378644e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>20140909</td>\n",
       "      <td>2.605495e+08</td>\n",
       "      <td>3.117394e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>20140910</td>\n",
       "      <td>2.498886e+08</td>\n",
       "      <td>3.140408e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>20140911</td>\n",
       "      <td>2.309412e+08</td>\n",
       "      <td>2.954018e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>20140912</td>\n",
       "      <td>1.927886e+08</td>\n",
       "      <td>2.849029e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>20140913</td>\n",
       "      <td>1.403980e+08</td>\n",
       "      <td>2.310117e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>20140914</td>\n",
       "      <td>1.469320e+08</td>\n",
       "      <td>2.499246e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>20140915</td>\n",
       "      <td>2.533344e+08</td>\n",
       "      <td>3.390640e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>20140916</td>\n",
       "      <td>2.553203e+08</td>\n",
       "      <td>3.129390e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>20140917</td>\n",
       "      <td>2.446593e+08</td>\n",
       "      <td>3.152404e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>20140918</td>\n",
       "      <td>2.257119e+08</td>\n",
       "      <td>2.966014e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>20140919</td>\n",
       "      <td>1.875593e+08</td>\n",
       "      <td>2.861025e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>20140920</td>\n",
       "      <td>1.351687e+08</td>\n",
       "      <td>2.322113e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>20140921</td>\n",
       "      <td>1.417028e+08</td>\n",
       "      <td>2.511242e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>20140922</td>\n",
       "      <td>2.481052e+08</td>\n",
       "      <td>3.402636e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>20140923</td>\n",
       "      <td>2.500910e+08</td>\n",
       "      <td>3.141386e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>20140924</td>\n",
       "      <td>2.394300e+08</td>\n",
       "      <td>3.164401e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>20140925</td>\n",
       "      <td>2.204826e+08</td>\n",
       "      <td>2.978010e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>20140926</td>\n",
       "      <td>1.823300e+08</td>\n",
       "      <td>2.873021e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>20140927</td>\n",
       "      <td>1.299395e+08</td>\n",
       "      <td>2.334109e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>20140928</td>\n",
       "      <td>1.364735e+08</td>\n",
       "      <td>2.523238e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>20140929</td>\n",
       "      <td>2.428759e+08</td>\n",
       "      <td>3.414632e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>20140930</td>\n",
       "      <td>2.448617e+08</td>\n",
       "      <td>3.153382e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds  purchase_amt    redeem_amt\n",
       "427  20140901  2.637930e+08  3.366648e+08\n",
       "428  20140902  2.657788e+08  3.105398e+08\n",
       "429  20140903  2.551178e+08  3.128412e+08\n",
       "430  20140904  2.361704e+08  2.942022e+08\n",
       "431  20140905  1.980179e+08  2.837033e+08\n",
       "432  20140906  1.456273e+08  2.298121e+08\n",
       "433  20140907  1.521613e+08  2.487250e+08\n",
       "434  20140908  2.585637e+08  3.378644e+08\n",
       "435  20140909  2.605495e+08  3.117394e+08\n",
       "436  20140910  2.498886e+08  3.140408e+08\n",
       "437  20140911  2.309412e+08  2.954018e+08\n",
       "438  20140912  1.927886e+08  2.849029e+08\n",
       "439  20140913  1.403980e+08  2.310117e+08\n",
       "440  20140914  1.469320e+08  2.499246e+08\n",
       "441  20140915  2.533344e+08  3.390640e+08\n",
       "442  20140916  2.553203e+08  3.129390e+08\n",
       "443  20140917  2.446593e+08  3.152404e+08\n",
       "444  20140918  2.257119e+08  2.966014e+08\n",
       "445  20140919  1.875593e+08  2.861025e+08\n",
       "446  20140920  1.351687e+08  2.322113e+08\n",
       "447  20140921  1.417028e+08  2.511242e+08\n",
       "448  20140922  2.481052e+08  3.402636e+08\n",
       "449  20140923  2.500910e+08  3.141386e+08\n",
       "450  20140924  2.394300e+08  3.164401e+08\n",
       "451  20140925  2.204826e+08  2.978010e+08\n",
       "452  20140926  1.823300e+08  2.873021e+08\n",
       "453  20140927  1.299395e+08  2.334109e+08\n",
       "454  20140928  1.364735e+08  2.523238e+08\n",
       "455  20140929  2.428759e+08  3.414632e+08\n",
       "456  20140930  2.448617e+08  3.153382e+08"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result['ds']=result['ds'].apply(lambda x:str(x).replace('-','')[0:8])\n",
    "result#这样做 后面的0000000都显示出来了  不需要  所以只需要前8位"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_csv('n_prophet.csv',header=None,index=False)"
   ]
  }
 ],
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